DETAILED ACTION
This action is in response to communications filed 01/22/2026. Claims 1, 2, 4, 13, 14, 17, and 20 have been amended, no new claims have been added, no claims have been cancelled. Claims 1-20 are presented for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Rejection of Claims 1-20 under 35 U.S.C. §112
The claims have been amended to remove the limitations previously cited for failing to comply with the written description requirement under 35 U.S.C. § 112(a).
The amendment renders the rejection no longer applicable and therefore the rejection has been withdrawn.
The applicant has amended the claims in response to the rejection set forth under 35 U.S.C. § 112(b).
The amendments are satisfactory and resolve the outstanding issues. The rejection has been withdrawn.
Advisory Action Assertions of Indefiniteness
The applicant has amended the claim in response to the assertions of indefiniteness presented in the advisory action dated January 15, 2026 and argues that when read in light of the specification, the claim is definite.
Applicant’s argument , in conjunction with the amendment to the claim, has been considered and is persuasive such that the limitation “exhibiting a thermal mass and cooling
duration that the predictive model identifies as exceeding a baseline thermal behavior
of the injection mold part” sets forth a clear boundary of the claim, when read in light of the specification.
Rejection of Claims 1-20 under 35 U.S.C. § 101
Applicant has amended the claims and submits that the claims as a whole are not directed to an abstract idea. Particularly, the applicant notes that the amended claim now requires “the conformal cooling arrangement is determined based on the identified hotspots” and that the hotspot identification directly determines the physical structure of the cooling channels to be manufactured. Applicant further argues that the physical formation of the mold insert with embedded sensors and conformal cooling arrangements are concrete, tangible manufacturing steps which cannot be performed as a mental process.
The introduction of the limitation “determining the conformal cooling arrangement based on the identified hotspots” is an additional recitation of a mental process because a human being can take identified information and use such information to make a further judgement about a design. This can be done using pen and paper as assistive aids so as to draw the arrangement. While the manufacturing steps to form the designed mold insert are indeed a physical step of the claim, the limitations of manufacturing the mold insert and using the mold insert appear to be recitations of merely applying the optimized design to a manufacturing process that is limited to a particular technological environment.
The applicant submits that the claims as amended are directed to solving the specific technological problem of thermal management in injection molding operations through coordinated design and manufacture of mold inserts.
Any purported improvement appears to be a direct result of the improvement of the mental process (optimal conformal cooling channel design in an insert) - seeing as how the optimized design is what drives the improvement (optimal design would yield optimal results) and the design process is one that can be performed mentally but is instead recited as being assisted by generic computing components.
The applicant asserts that the amendment requiring that “the conformal cooling arrangement is determined based on the identified hotspots” directly addresses the examiner’s Mere Instructions to Apply an Exception (MPEP 2106.05(f)) concern because the computation step allegedly is no longer merely using a computer to perform thermal modeling but is now an integral step that determines the physical configuration of the manufactured mold insert.
The newly-added limitation does not address the Mere Instructions to Apply an Exception (MPEP 2106.05(f)) because the claim still amounts to using a generic computing component (predictive model/simulator) to identify hotspots, which could be done as a mental process. And furthermore the determination of the cooling arrangement based on the hotspots is likewise a process that can be performed mentally but is instead as being performed “automatically” such that the claim reads is invoking the use of a computer to perform the recited exception.
The applicant argues that the amended claims recite specific technological elements that result in improved cooling performance and manufacturing efficiency.
This improvement is not reflected in the claim. Using a predictive thermal model to identify hotspots amounts to using a generic computer to enable the performance of a mental process. Determining the cooling arrangement based on the hotspots is additionally a recitation of a mental process. Embedding physical sensors to measure temperature, pressure, and mold cycle events but not clearly linking any benefit provided by their insertion is linking the judicial exception to a particular technological environment but does not necessarily provide an inventive concept because it is not apparent that the sensors may be employed or used in an inventive manner. That is-placing them within the insert doesn’t readily provide an improvement itself. Forming the mold insert with the conformal cooling arrangement is the recitation of merely applying the optimal design obtained as part of the steps construed as a mental process. The improvement appears to be rooted in determining the optimal design, wherein the design process is being read as a mental process that leverages generic computing components. An improvement to a mental process is not an improvement in technology.
Applicant submits that the claims are directed to improving the physical process of injection molding through enhanced thermal management.
The claims to do not reflect an improvement to the physical injection molding process. The injection molding process appears to be recited as occurring in its ordinary and expected capacity. The optimized design of the cooling arrangement is what yields any alleged improvement. Per MPEP 2106.05(a) “It is important to note, the judicial exception alone cannot provide the improvement.“ but rather the improvement must be provided by the additional elements or the additional elements in conjunction with the judicial exception.
Applicant argues that the amended claims introduce a functional relationship between a computational analysis and the physical structure being manufactured because the claims require that identified hotspots directly determine the conformal cooling arrangement that is subsequently manufactured through an additive manufacturing process. Applicant further asserts that the manufacturing and use steps cannot be performed mentally and represent concrete improvement to injection molding technology.
While the examiner agrees that the manufacturing and use steps cannot be performed mentally, the examiner does not agree that such steps represent concrete improvements to injection molding technology. Firstly, using additive manufacturing for forming injection molding inserts is demonstrated as being well understood, in at least by Metal AM (Metal AM, “Conformal cooling: How AM is increasing efficiency and quality in the injection moulding industry”, Sept 1, 2018, metal-am.com), hereinafter referred to as Metal AM which describes its usage dating back to the 1990’s. ((Metal AM, ¶1) "Additive Manufacturing has been used to build moulds incorporating conformal cooling channels since the 1990s when the first metal powder-based AM systems came to market. "). Secondly, using an injection mold insert to cool material and form the injection mold part in an injection mold process is likewise typical in the industry, as given by evidence of the specification in at least ¶3. Accordingly, these additional limitations do not provide an inventive concept, nor does their relationship with the recited judicial exception. The limitations merely amount to applying the optimized design in a way that has been demonstrated to be well understood and routine and do not provide improvements to injection molding technology.
Applicant further points to the specification to reference the following: “As-Filed
Specification, paragraph [0046]. The specification further explains that "[b ]y creating conformal
cooling channels that follow the unique geometry in the mold tool of an injection molded part,
engineers can perfectly optimize their cooling lines resulting reduced cooling times and decreased potential for quality issues such as warping." As-Filed Specification, paragraph [0044].” In this same argument, the applicant submits that these improvements are technological in nature and not an improvement in a mental process.
Contrarily, the applicant has admitted that engineers can perfectly optimize their cooling lines which is what results in reduced cooling times and decreased quality issues. This statement is an admission of two things: 1. If an engineer can optimize the cooling line, the process is that which can be performed mentally. And 2. The improvements presented by the claimed invention are provided by the mental process itself.
The applicant further argues that the amended claim requires a particular sequence of steps that work together to achieve the technological improvement, particularly noting that the determination of the identified hotspots ensures the computational step has a direct required effect on the physical structure being manufactured. While the design may indeed dictate what is manufactured per the design, the determination of the cooling arrangement based on the hotspots is that which can be read as a mental process, as stated previously. Again, the improvement can not be provided by the mental process.
Applicant argues that the Examiner’s conclusion drawn in the previous office action is not effectively supported by the record and notes that the specification makes clear that the claimed invention represents an unconventional approach to injection mold cooling because conventional insert formation techniques rely on gun drilling to form cooling channels and are incapable of following the geometry of the part. Rather, the claimed invention requires channels constructed and arranged to include curved paths or other geometries to reach high-temperature areas.
While gun drilling is recognized as a conventional technique for forming cooling inserts, conformal cooling channels formed by additive manufacturing is alternatively a well understood methodology by which to achieve desired cooling in inserts. This is given as evidence presented by AM Metals, as noted above and restated here for ease of reference. ((Metal AM, ¶1) "Additive Manufacturing has been used to build moulds incorporating conformal cooling channels since the 1990s when the first metal powder-based AM systems came to market. "). Accordingly such conclusion is supported by this evidence.
Applicant argues that the combination of a predictive thermal model to identify hotspots, determination of sensor locations based on hotspots, and the additive manufacturing of mold inserts with embedded sensors positioned in the hotspots represents an unconventional and inventive approach. The applicant notes the specification, citing proprietary predictive engineering models.
However, the claims do not reference the predictive models in any capacity such that an inventive nature of them is apparent. A predictive model and even a predictive thermal model are recited at such high levels of generality that the particular model or any improvement within said model is not readily apparent by the claims. The generic nature of the predictive model amounts to using generic computing components as tools to enable the performance of the judicial exception- that is using the predictive model to determine hotspots and sensor placement. The courts do not distinguish between mental processes performed entirely in the human mind, those performed using pen and paper as assistive physical aids, and those performed on a computer. Accordingly, the inclusion of the predictive model does not prevent an inventive concept when used in conjunction with the recited judicial exception.
The applicant argues that the Examiner has not provided an adequate explanation as to why the claimed elements to not amount to significantly more when recited with the judicial exception.
The Final office action characterizes the additional elements as being Mere Instructions to Apply an Exception (MPEP 2106.05(f)), Insignificant Extra Solution Activity (MPEP 2106.05(g)), and Field of Use and Technological Environment (MPEP 2106.05(h)). These classifications have been found by the courts to be not enough to amount to significantly more than the abstract idea. The court’s decision is an adequate explanation- see MPEP 2106.05(A). When viewing the claim as a whole, the relationships between the recited judicial exceptions and the additional elements do not present an inventive concept because the claim as a whole appears to be using generic computing components recited at a high level of generality to perform a judicial exception, wherein the judicial exception is what provides the inventive concept. The output of the inventive concept is applied to a technological environment in a way that is well-understood and does not provide an inventive concept, as stated throughout this response.
The applicant argues that using a predictive model to identify hotspots for determining sensor locations is not a conventional practice.
While this may not be a conventional practice, at least for the sake of argument, the practice is a judicial exception enabled by generic computing components. Mental processes or any recited judicial exception are not evaluated for being well understood, routine, or conventional.
The applicant argues that the integration of embedded sensors positions based on the hotspots represents an unconventional combination. The applicant points to the specification, noting that the specification alleges the feedback loop driven by sensors positioned at location corresponding to hotspots enables continuous improvement of the predictive model. The applicant further submits that this represents a specific technological solution not found in the prior art.
Per MPEP 2106.05(a), an important consideration in determining whether a claim improves technology is the extent to which a claim covers a particular solution to a problem or a particular way to achieve a desired outcome or solution as opposed to merely claiming the idea of a solution or outcome. The claim and specification set forth an idea of a solution or outcome without explicitly setting forth the steps by which to achieve such outcome. Claim 2 recites that the sensor is embedded at the one or more sensor locations for providing a feedback loop that modifies a result of the predictive model. It is not apparent through the claim or the specification how this feedback from the sensor is used so as to modify a result of the predictive model. Accordingly, the limitation does not provide a particular solution to a particular problem.
The applicant further argues that the manufacturing approach is unconventional.
As stated previously in this action, the manufacturing approach has been found by the evidence to be at least well understood within the art.
Based on the rationale provided in this response, in conjunction with the updated rejection of this action, the claims remain rejected under 35 U.S.C. § 101.
Rejection of claims 1, 4, 5, 11-13, 15, 16, and 20 under 35 U.S.C. § 103
Applicant has amended the claims and argues that Hadar and Park, individually or in combination, do not disclose or suggest a predictive model that automatically identifies hotspots comprising regions of the injection mold part exhibiting a thermal mass and cooling duration as quantified by the predictive model, per the amended claims.
Applicant’s arguments have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument. Rather, Patel is relied upon to disclose the newly-added features, as stated in this action. In particular, Patel discloses an automated methodology to predict an optimal insert for an injection molding process, wherein the automated methodology comprises thermal simulations wherein hotspots are identified. The thermal simulation is based on equations which model the cooling stage of the material ((Patel, Page 3, Lines 33-36) " In particular, the simulation of the injection molding process may be based on sets of equations which model the respective stages of the injection molding process: 1) The flow of material through the input gates into the cavity; 2) the cooling process of the material;") and the modeled process parameters have consideration for a cooling schedule as the cooling duration ((Patel, Page 5, Lines 36-38 and Page 6 Lines 1-4) " As is apparent from the above description, the simulated process depends on properties (geometry, choice of material, etc.) of the mold component as well as on a number of additional molding process parameters. Examples of the molding process parameters may include one or more of the following - A cooling schedule for cooling the molded part, e.g. as defined by the temperature and flow of coolant through the cooling channels of the mold insert and/or other component of the mold;"). The equations by which the simulation is performed considers the heat capacity of the material by which the thermal mass may be derived ((Patel, Page 4, Lines 1-10) " The model for the filling process may be based on suitable material flow equations for each of the volume elements describing the inflow and outflow of material into/from the volume element from/to the respective neighboring volume elements. The model for the filling process may further comprise suitable heat transport equations for each of the volume elements describing the inflow and outflow of heat into/from the volume element from/to the respective neighboring volume elements and (for the volume elements adjacent to the cavity walls) to/from the cavity walls. These equations are dependent on material properties of the material from which the part is to be molded, such as viscosity, heat conductivity, heat capacity, etc."). Further, the optimization process evaluates the simulation results with regard for predefined tolerance values, which may include a cycle time indicative of thermal behavior ((Patel, Page 15, Lines 18-32) " Subsequently, the optimizer engine executes simulator 115 to perform a simulation of the injection molding process based on the mold insert model created by the simulator 112 and from associated molding parameters, such as choice of material, temperature, pressure, etc. The simulation of the injection molding process results in a model of the injection molded part. It will be appreciated that the simulation process may be an iterative process where various process parameters and/or the mold insert model may iteratively be modified so as to optimize for one or more parameters, such as manufacturing tolerances, cycle time, etc. In particular, the optimizer engine may compare the model of the molded part which results from the simulation with the originally received CAD model of the part to be injection molded so as to estimate the tolerances. If the model of the injection molded part shows that the injection molded part lies outside the target tolerances, the optimizer engine may alter the mold insert model and/or the process parameters and execute simulator 115 again based on the modified model and/or process parameters. The optimizer engine may even execute both simulators 112 and 115 again.")
Applicant further argues that the embedded sensors recited in the amended claims are not passive monitoring components but are structurally and functionally integrated into the manufacturing process. Applicant further argues that Hadar nor the other cited references teach this integrated closed-loop approach where hotspot identification drives both physical cooling channel design and sensor-based validation/feedback system.
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., "a feedback loop to ensure that the modeling capabilities continue to improve" and that "[t]his information can then be correlated to the data from the predictive engineering model to validate and improve it over time.") are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). While the feature does appear to be claimed more explicitly in Claim 2, the argument presented is in regard to those features being claimed within Claim 1. It should be noted; however, even in looking at Claim 2 which has such features, the limitations are fairly taught by the reference Kumar, which suggests incorporating sensor data from an injection molding process for predictive model validation purposes.
The applicant further argues that hotspot identification influencing cooling channel design and the sensor-based validation/feedback system is not disclosed by the art. Specifically, applicant argues “In contrast, claim I as amended requires that "the cooling channel geometries and routing paths are automatically derived from the hotspot locations"-establishing a mandatory causal link where the hotspot analysis output directly and automatically determines the physical cooling channel design.”
This argument is moot in light of the teachings of Patel, wherein Patel demonstrates an iterative and automated computer based optimization process for an insert design that incorporates reliance on the identification of hotspots into such process. The claim does not require particularly how the identified hotspots dictate the conformal cooling arrangement in any capacity that would distinguish the present claims from the teachings of Patel (that incorporate a loose reliance on the hotspots, demonstrated at least most apparently by interdependence of optimization steps).
The applicant argues that the identified hotspots have a concrete effect on the physical structure being manufactured- that the cooling channels must be routed in proximity to the hotspots and that Hadar does not disclose this feature.
The argument is moot based on the new grounds of rejection wherein Patel discloses the recognition of hotspots in the optimization process during at least a step of the optimization and subsequently produces an optimized insert design after such step, thereby at least indicating influence of identification to design. While the claim requires that routing channels occur in proximity to identified hotspots, there is no clear feature between that claimed in the present claims and that disclosed by Patel which would indicate a certain, identifiable proximity definition. Under broadest reasonable interpretation, proximity may involve any distance to the identified hotspots. By Patel, hotpsots are at least identified in the mold insert during the simulation and the cooling channels are routed within the mold insert. By association of both occurring at the mold insert, they are thereby assumed to be in proximity to one another.
The applicant argues that the prior art does not disclose or suggest a manufacturing step where the cooling channels in the physical metal mold insert are routed in proximity to identified hotspots.
This argument is moot based on the new grounds set forth under Patel, wherein Patel suggests an additive manufacturing process by which to form the mold insert which is described and suggested as having conformal cooling channels.
The applicant further argues that the Examiner has not explained why one of skill in the art would have been motivated to modify the teachings of the prior art to arrive at the technological process recited in the amended claims.
A prima facie case of obviousness has been presented for the current claim set per this action, wherein a new grounds of rejection has been set forth on the combined teachings of Patel and Park.
Rejection of Claims 2, 3, 6, 7, 8, 9, 10, 14 , 17, 18, and 19 under 35 U.S.C. §103
Applicant argues that the references relied upon for the dependent claims do not cure the deficiencies of the combined teachings of Hadar, Gao, and Park.
These arguments are moot, based on the new ground of rejection set forth in this action which relies on Patel to cure such deficiencies of the prior art to teach the newly introduced claim limiations.
Claim Objections
Claim 1, 13, and 20 are objected to because of the following informalities:
Claims 1, 13, and 20 recites “automatically iteratively refining the conformal cooling arrangement” which should instead read “automatically, iteratively refining the conformal cooling arrangement”.
Claim 13 recites “executing the predictive model simulates thermal behavior of the injection mold part and automatically identify hotspots” which does not appear to be grammatically correct. The language should reflect that as described in claim 1 which is written correctly. (“executing the predictive model to simulate thermal behavior of the injection mold part and automatically identify hotspots”)
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 1 recites the limitation "hotspot locations" in line 13. There is insufficient antecedent basis for this limitation in the claim. It appears as though this claim element is referring to the identified hotspots comprising regions of the injection mold part exhibiting… as given in lines 7-8 of Claim 1. It is not absolutely certain that the regions of the hotspots are synonymous with the location of the hotspots.
Claim 1 recites the limitation "the cooling channel design" in line 15. There is insufficient antecedent basis for this limitation in the claim. “a design of an injection mold part” is introduced in line 3 and “conformal cooling arrangement” is introduced in lines 4-5. It is unclear what the design is particularly referring to. For purposes of this examination, the cooling channel design is interpreted as the conformal cooling arrangement.
Claims 2-12 incorporate the deficiencies of claim 1 and are rejected under the same rationale.
Claim 4 recites “the design” in lines 2 and 3-4. In claim 1 from which claim 4 depends, “a design of an injection mold part” and “the cooling channel design” are introduced in the claim. It is unclear what aspect of “the design” is being referred to in claim 4.
Claim 5 incorporates the deficiency of claim 4.
Claim 5 recites “a design of conformal cooling lines” in line 2. It is unclear if this element is distinct or the same as that referenced in claim 1 from which claim 5 depends, wherein claim 1 recites “the cooling channel design” in line 15.
Claim 6 recites “the design” in line 1. In claim 1 from which claim 6 depends, “a design of an injection mold part” and “the cooling channel design” are introduced in the claim. It is unclear what aspect of “the design” is being referred to in claim 6.
Claim 7 recites “the design” in line 3. In claim 1 from which claim 7 depends, “a design of an injection mold part” and “the cooling channel design” are introduced in the claim. It is unclear what aspect of “the design” is being referred to in claim 7.
Claim 13 recites the limitation "the cooling channel geometries and routing paths" in line 11. There is insufficient antecedent basis for this limitation in the claim.
Claim 13 recites the limitation "hotspot locations" in line 12. There is insufficient antecedent basis for this limitation in the claim. It appears as though this claim element is referring to the identified hotspots comprising regions of the injection mold part exhibiting… as given in lines 6-7 of Claim 13. It is not absolutely certain that the regions of the hotspots are synonymous with the location of the hotspots.
Claim 13 recites the limitation "the cooling channel design" in line 14. There is insufficient antecedent basis for this limitation in the claim. “a design of an injection mold part” is introduced in line 2 and “conformal cooling arrangement” is introduced in lines 3-4. It is unclear what the design is particularly referring to. For purposes of this examination, the cooling channel design is interpreted as the conformal cooling arrangement.
Claims 14-19 incorporate the deficiencies of claim 13 and are rejected under the same rationale.
Claim 15 recites “the design” in lines 1-2 and line 3. In claim 13 from which claim 15 depends, “a design of an injection mold part” and “the cooling channel design” are introduced in the claim. It is unclear what aspect of “the design” is being referred to in claim 15.
Claim 16 incorporates the deficiencies of claim 15.
Claim 16 recites “a design of conformal cooling lines” in line 2. It is unclear if this element is distinct or the same as that referenced in claim 13 from which claim 16 depends, wherein claim 13 recites “the cooling channel design” in line 14.
Claim 17 recites “the design” in line 1. In claim 13 from which claim 17 depends, “a design of an injection mold part” and “the cooling channel design” are introduced in the claim. It is unclear what aspect of “the design” is being referred to in claim 17.
Claim 20 recites the limitation "the cooling channel geometries and routing paths" in line 11. There is insufficient antecedent basis for this limitation in the claim.
Claim 20 recites the limitation "hotspot locations" in line 12. There is insufficient antecedent basis for this limitation in the claim. It appears as though this claim element is referring to the identified hotspots comprising regions of the injection mold part exhibiting… as given in lines 7-8 of Claim 20. It is not absolutely certain that the regions of the hotspots are synonymous with the location of the hotspots.
Claim 20 recites the limitation "the cooling channel design" in line 14. There is insufficient antecedent basis for this limitation in the claim. “a design of an injection mold part” is introduced in line 2 and “conformal cooling arrangement” is introduced in lines 3-4. It is unclear what the design is particularly referring to. For purposes of this examination, the cooling channel design is interpreted as the conformal cooling arrangement.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-7, 9-17, and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The following section follows the 2019 Patent Eligibility Guidance (PEG) for analyzing subject matter eligibility:
Step 1 - Statutory Category:
Step 1 of the PEG analysis entails considering whether the claimed subject matter falls within the four statutory categories of patentable subject matter identified by 35 U.S.C. 101 (process, machine, manufacture, or composition of matter).
Step 2A Prong 1 - Judicial exception:
In Step 2A Prong 1, examiners evaluate whether the claim recites a judicial exception (an abstract idea, law of nature, or a natural phenomenon).
Step 2a Prong 2 - Integration into a practical application:
If claims recite a judicial exception, the claim requires further analysis in Step 2A Prong 2. In Step 2A Prong 2, examiners evaluate whether the claim as a whole integrates the exception into a practical application.
Step 2B - Significantly More:
If the additional elements identified in Step 2A Prong 2 do not integrate the exception into a practical application, then the claim is directed to the recited judicial exception and requires further analysis under Step 2B- Significantly More.
As noted in the MPEP 2106.05(II): The identification of the additional element(s) in the claim from Step 2A Prong 2, as well as the conclusions from Step 2A Prong 2 on the considerations discussed in MPEP 2106.05(a) -(c), (e), (f), and (h) are to be carried over. Claim limitations identified as Insignificant Extra-Solution Activities are further evaluated to determine if the elements are beyond what is well -understood, routine, and conventional (WURC) activity, as dictated by MPEP 2106.05(II).
The additional elements are then evaluated to determine if any additional element or combination of elements are other than what is well-understood, routine, conventional activity in the field, or simply append well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, per MPEP § 2106.05(d).
Independent Claims:
Claim 1:
Step 1: Claim 1 and its dependent claims 2-12 are directed to a method which falls within one of the four statutory categories of a process.
Step 2A Prong 1: Claim 1 recites a judicial exception, noted in bold:
analyzing, …, the design to determine a conformal cooling arrangement for a mold insert for forming the injection mold part;. The claim limitation can be reasonably read to entail evaluating the design to determine a cooling arrangement for a mold insert. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim limitation recites the use of a predictive model to perform this process, which is recited as a computing component at a high level of generality. The courts do not distinguish between judicial exceptions performed entirely in the human mind and those performed on a computer.
identify hotspots, the hotspots comprising regions of the injection mold part exhibiting a thermal mass and cooling duration that …identifies as exceeding a baseline thermal behavior of the injection mold part;. The claim limitation can be reasonably read to entail observing and evaluating thermal behavior of an injection molding part so as to make a judgment on hotspot regions of the part. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim limitation recites the use of a predictive model to perform this process, which is recited as a computing component performing functions at a high level of generality (simulate/automatically identify). The courts do not distinguish between judicial exceptions performed entirely in the human mind and those performed on a computer.
determining the conformal cooling arrangement based on the identified hotspots, The claim limitation can be reasonably read to entail evaluating the identified hotspots so as to inform a judgment to an appropriate conformal cooling arrangement. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
wherein cooling channel geometries and routing paths are … derived from the hotspot locations, The claim limitation can be reasonably read to entail evaluating the hotspot locations and using them as a basis for forming a judgment for the cooling channel geometries and routing paths. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim recites this limitation as being performed automatically, thereby indicating the employment of a computer to perform the task. The courts do not distinguish between mental process that may be performed entirely in the human mind or employ the use of generic computers to perform the process.
iteratively refining the conformal cooling arrangement by … that accounts for the cooling channel design to identify any remaining hotspots and further optimize the cooling channel geometries; This claim limitation can be reasonably read to entail evaluating the conformal cooling arrangement and making judgments for ways to improve the arrangement by accounting for the previous deisgn. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim recites the use of an additional predictive thermal model to perform this process which appears to be a generic computing component recited at a high level of generality to perform the process. The courts do not distinguish between mental processes performed entirely in the human mind and those which employ generic computers to execute the process.
determining sensor locations within the mold insert for embedding at least one sensor configured to measure one or more of temperature, pressure, and mold cycle events at the sensor locations; This claim limitation can be reasonably read to entail making a judgment for sensor locations. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Therefore, the claim recites a judicial exception.
Step 2A Prong 2: Additional elements were identified and are noted in italics.
providing a design of an injection mold part;- This limitation has been identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) of mere data gathering.
by a predictive model- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
executing the predictive model to simulate thermal behavior of the injection mold part and automatically … the predictive model- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
automatically - This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
automatically - This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
executing an additional predictive thermal model - This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
manufacturing the mold insert by adding material one layer at a time to form the conformal cooling arrangement and the at least one embedded sensor within a metal structure of the mold insert, wherein the conformal cooling arrangement comprises cooling channels routed in proximity to the identified hotspots; and- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for amounting to the words “apply it” with regard to the judicial exception. The limitation has also been identified as Field of Use and Technological Environment (MPEP 2106.05(h)) for linking the use of the judicial exception to a particular technological environment.
using the mold insert in an injection molding process to form the injection mold part.- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for amounting to the words “apply it” with regard to the judicial exception.
The courts have found that merely including instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea or reciting the words “apply it” with the judicial exception (Mere Instructions to Apply an Exception (MPEP 2106.05(f))); adding insignificant extra- solution activity to the judicial exception (Insignificant Extra Solution Activity (MPEP 2106.05(g))); and generally linking the use of a judicial exception to a particular technological environment or field of use (Field of Use and Technological Environment (MPEP 2106.05(h))) does not integrate the judicial exception into a practical application.
When viewed independently and within the claim as a whole, the additional element does not appear to integrate the judicial exception into a practical application because the claim does not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The way in which the additional elements interact with the judicial exception(s) appear to be using generic computing components recited at a high level of generality to enable the performance of a task which can be performed in the human mind or using pen and paper as assistive physical aids. Further, the additional elements appear to employ insignificant extra solutionary activity to obtain a design by which to perform the judicial exception on and recite steps of merely applying the judicial exception in a particular technological environment.
Step 2B: As discussed in Step 2A Prong 2, additional elements were identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) which must be further evaluated to determine if they are beyond WURC activities. Additional elements identified otherwise and conclusions from Step 2A Prong 2 are carried over for evaluating if the claim, as a whole, amounts to an inventive concept that is significantly more than the judicial exception:
providing a design of an injection mold part;- This limitation has been identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) of mere data gathering. Under broadest reasonable interpretation and when read in light of the specification, this additional element entails sending a receiving data over a network. This computer function has been found by the courts to be well understood, routine, and conventional when claimed in a merely generic manner such as in the claim.
The courts have found that simply appending insignificant extra solution activities that are well-understood, routine, and conventional activities to the judicial exception does not qualify the limitations as “significantly more” than the recited judicial exception. The remaining additional elements were identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) and Field of Use and Technological Environment (MPEP 2106.05(h)), as stated previously. The courts have found that merely using a computer as a tool to perform a mental process and generally linking the use of a judicial exception to a particular technological environment does not qualify the limitations as “significantly more” than the recited judicial exception.
With the additional elements viewed independently and as part of the ordered combination, the claim as a whole does not appear to amount to significantly more than the recited judicial exception because the claim is using generic computing components recited at a high level of generality and functioning in their normal capacity in conjunction with well-understood, routine, and conventional activity to enable the performance of a task that can practically be performed within the human mind or using pen and paper as an assistive physical aid. The claim further appears to link the use of the judicial exception to a particular technological environment by reciting additional well-understood, routine, and conventional activities within the art paired with the judicial exception as a mechanism by which to apply the judicial exception in a non-inventive way.
For example, reciting that something is performed “automatically” and/or by a “predictive model” which is not described beyond a high level of generality does not present anything beyond what is well understood, routine and conventional. This is given as evidence by the court’s findings that mere instructions to implement an abstract idea on a computer is not enough to amount to significantly more than the recited judicial exception (MPEP 2106.05(I)(A). The particularity of the machine or apparatus used to implement the design optimization is not specifically identifiable by the claim language such that the claim would demonstrate the use of a particular machine. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine.
Furthermore, applying an additive manufacturing process according to the optimized insert design to fabricate the designed insert is not beyond what has been recognized as well understood in the art. Such a process, at least at the level recited by the claim, has been in use since the 1990s, as given by Metal AM (Metal AM, “Conformal cooling: How AM is increasing efficiency and quality in the injection moulding industry”, Sept 1, 2018, metal-am.com), hereinafter referred to as Metal AM which describes its usage dating back to the 1990’s. ((Metal AM, ¶1) "Additive Manufacturing has been used to build moulds incorporating conformal cooling channels since the 1990s when the first metal powder-based AM systems came to market. "). There are no such limitations in the claim that distinguish this process in any inventive capacity beyond what is well known already in the art. While the claim does recite that an embedded sensor occur within the manufactured mold insert, its inclusion, at least based on the claim language, does not demonstrate an improvement to the technology for at least failing to recite in how the sensor is used in any meaningful capacity besides its intended use (temperature, pressure, etc).
Lastly, the claim recites “using the mold insert in an injection molding process to form the injection mold part”. As given by the specification, using mold inserts in injection molding process is typical in the art (See at least ¶3 of the specification). This evidence further supports that using an insert in an injection molding process in an unspecified way beyond its ordinary capacity is a well understood, routine, and conventional task in the art.
Therefore, the claim does not include additional elements, alone or in combination that are sufficient to amount to significantly more than the recited judicial exception.
Conclusion: Based on this rationale, the claim has been deemed to be ineligible subject matter under 35 U.S.C. 101.
Claim 13:
Step 1: Claim 13 and its dependent claims 14-19 are directed to a method which falls within one of the four statutory categories of a process.
Step 2A Prong 1: Claim 13 recites a judicial exception, noted in bold:
analyzing, …, the design to determine a conformal cooling arrangement for a mold insert for forming the injection mold part;. The claim limitation can be reasonably read to entail evaluating the design to determine a cooling arrangement for a mold insert. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim limitation recites the use of a predictive model to perform this process, which is recited as a computing component at a high level of generality. The courts do not distinguish between judicial exceptions performed entirely in the human mind and those performed on a computer.
identify hotspots, the hotspots comprising regions of the injection mold part exhibiting a thermal mass and cooling duration that …identifies as exceeding a baseline thermal behavior of the injection mold part;. The claim limitation can be reasonably read to entail observing and evaluating thermal behavior of an injection molding part so as to make a judgment on hotspot regions of the part. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim limitation recites the use of a predictive model to perform this process, which is recited as a computing component performing functions at a high level of generality (simulate/automatically identify). The courts do not distinguish between judicial exceptions performed entirely in the human mind and those performed on a computer.
determining the conformal cooling arrangement based on the identified hotspots, The claim limitation can be reasonably read to entail evaluating the identified hotspots so as to inform a judgment to an appropriate conformal cooling arrangement. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
wherein the cooling channel geometries and routing paths are … derived from the hotspot locations, The claim limitation can be reasonably read to entail evaluating the hotspot locations and using them as a basis for forming a judgment for the cooling channel geometries and routing paths. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim recites this limitation as being performed automatically, thereby indicating the employment of a computer to perform the task. The courts do not distinguish between mental process that may be performed entirely in the human mind or employ the use of generic computers to perform the process.
iteratively refining the conformal cooling arrangement by … that accounts for the cooling channel design to identify any remaining hotspots and further optimize the cooling channel geometries; This claim limitation can be reasonably read to entail evaluating the conformal cooling arrangement and making judgments for ways to improve the arrangement by accounting for the previous deisgn. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim recites the use of an additional predictive thermal model to perform this process which appears to be a generic computing component recited at a high level of generality to perform the process. The courts do not distinguish between mental processes performed entirely in the human mind and those which employ generic computers to execute the process.
determining sensor locations within the mold insert for embedding at least one sensor configured to measure one or more of temperature, pressure, and mold cycle events at the sensor locations; This claim limitation can be reasonably read to entail making a judgment for sensor locations. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Therefore, the claim recites a judicial exception.
Step 2A Prong 2: Additional elements were identified and are noted in italics.
providing a design of an injection mold part;- This limitation has been identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) of mere data gathering.
by a predictive model- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
executing the predictive model simulates thermal behavior of the injection mold part and automatically … the predictive model- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
automatically - This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
automatically - This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
executing an additional predictive thermal model - This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
forming the mold insert including the conformal cooling arrangement and the at least one embedded sensor within the mold insert, wherein the conformal cooling arrangement comprises cooling channels routed in proximity to the identified hotspots; and- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for amounting to the words “apply it” with regard to the judicial exception. The limitation has also been identified as Field of Use and Technological Environment (MPEP 2106.05(h)) for linking the use of the judicial exception to a particular technological environment.
forming the injection mold part by heating a source of material at the mold insert and cooling the source of material by the conformal cooling arrangement.- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for amounting to the words “apply it” with regard to the judicial exception.
The courts have found that merely including instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea or reciting the words “apply it” with the judicial exception (Mere Instructions to Apply an Exception (MPEP 2106.05(f))); adding insignificant extra- solution activity to the judicial exception (Insignificant Extra Solution Activity (MPEP 2106.05(g))); and generally linking the use of a judicial exception to a particular technological environment or field of use (Field of Use and Technological Environment (MPEP 2106.05(h))) does not integrate the judicial exception into a practical application.
When viewed independently and within the claim as a whole, the additional element does not appear to integrate the judicial exception into a practical application because the claim does not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The way in which the additional elements interact with the judicial exception(s) appear to be using generic computing components recited at a high level of generality to enable the performance of a task which can be performed in the human mind or using pen and paper as assistive physical aids. Further, the additional elements appear to employ insignificant extra solutionary activity to obtain a design by which to perform the judicial exception on and recite steps of merely applying the judicial exception in a particular technological environment.
Step 2B: As discussed in Step 2A Prong 2, additional elements were identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) which must be further evaluated to determine if they are beyond WURC activities. Additional elements identified otherwise and conclusions from Step 2A Prong 2 are carried over for evaluating if the claim, as a whole, amounts to an inventive concept that is significantly more than the judicial exception:
providing a design of an injection mold part;- This limitation has been identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) of mere data gathering. Under broadest reasonable interpretation and when read in light of the specification, this additional element entails sending a receiving data over a network. This computer function has been found by the courts to be well understood, routine, and conventional when claimed in a merely generic manner such as in the claim.
The courts have found that simply appending insignificant extra solution activities that are well-understood, routine, and conventional activities to the judicial exception does not qualify the limitations as “significantly more” than the recited judicial exception. The remaining additional elements were identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) and Field of Use and Technological Environment (MPEP 2106.05(h)), as stated previously. The courts have found that merely using a computer as a tool to perform a mental process and generally linking the use of a judicial exception to a particular technological environment does not qualify the limitations as “significantly more” than the recited judicial exception.
With the additional elements viewed independently and as part of the ordered combination, the claim as a whole does not appear to amount to significantly more than the recited judicial exception because the claim is using generic computing components recited at a high level of generality and functioning in their normal capacity in conjunction with well-understood, routine, and conventional activity to enable the performance of a task that can practically be performed within the human mind or using pen and paper as an assistive physical aid. The claim further appears to link the use of the judicial exception to a particular technological environment by reciting additional well-understood, routine, and conventional activities within the art paired with the judicial exception as a mechanism by which to apply the judicial exception in a non-inventive way.
For example, reciting that something is performed “automatically” and/or by a “predictive model” which is not described beyond a high level of generality does not present anything beyond what is well understood, routine and conventional. This is given as evidence by the court’s findings that mere instructions to implement an abstract idea on a computer is not enough to amount to significantly more than the recited judicial exception (MPEP 2106.05(I)(A). The particularity of the machine or apparatus used to implement the design optimization is not specifically identifiable by the claim language such that the claim would demonstrate the use of a particular machine. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine.
Furthermore, applying insert forming process according to the optimized insert design to fabricate the designed insert with conformal cooling channels is not beyond what has been recognized as well understood in the art. Such a process, at least at the level recited by the claim, has been in use since the 1990s, as given by Metal AM (Metal AM, “Conformal cooling: How AM is increasing efficiency and quality in the injection moulding industry”, Sept 1, 2018, metal-am.com), hereinafter referred to as Metal AM which describes its usage dating back to the 1990’s. ((Metal AM, ¶1) "Additive Manufacturing has been used to build moulds incorporating conformal cooling channels since the 1990s when the first metal powder-based AM systems came to market. "). There are no such limitations in the claim that distinguish this process in any inventive capacity beyond what is well known already in the art. While the claim does recite that an embedded sensor occur within the manufactured mold insert, its inclusion, at least based on the claim language, does not demonstrate an improvement to the technology for at least failing to recite in how the sensor is used in any meaningful capacity besides its intended use (temperature, pressure, etc).
Lastly, the claim recites “forming the injection mold part by heating a source of material at the mold insert and cooling the source of material by the conformal cooling arrangement.”. As given by the specification, using mold inserts in injection molding process that heats material to inject into the mold is typical in the art (See at least ¶3-4 of the specification). This evidence further supports that using an insert in an injection molding process in an unspecified way beyond its ordinary capacity is a well understood, routine, and conventional task in the art.
Therefore, the claim does not include additional elements, alone or in combination that are sufficient to amount to significantly more than the recited judicial exception.
Conclusion: Based on this rationale, the claim has been deemed to be ineligible subject matter under 35 U.S.C. 101.
Claim 20:
Step 1: Claim 20 is directed to a part which falls within one of the four statutory categories of a manufacture.
Step 2A Prong 1: Claim 20 recites a judicial exception, noted in bold:
analyzing, …, the design to determine a conformal cooling arrangement for a mold insert for forming the injection mold part;. The claim limitation can be reasonably read to entail evaluating the design to determine a cooling arrangement for a mold insert. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim limitation recites the use of a predictive model to perform this process, which is recited as a computing component at a high level of generality. The courts do not distinguish between judicial exceptions performed entirely in the human mind and those performed on a computer.
identify hotspots, the hotspots comprising regions of the injection mold part exhibiting a thermal mass and cooling duration that …identifies as exceeding a baseline thermal behavior of the injection mold part;. The claim limitation can be reasonably read to entail observing and evaluating thermal behavior of an injection molding part so as to make a judgment on hotspot regions of the part. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim limitation recites the use of a predictive model to perform this process, which is recited as a computing component performing functions at a high level of generality (simulate/automatically identify). The courts do not distinguish between judicial exceptions performed entirely in the human mind and those performed on a computer.
determining the conformal cooling arrangement based on the identified hotspots, The claim limitation can be reasonably read to entail evaluating the identified hotspots so as to inform a judgment to an appropriate conformal cooling arrangement. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
wherein the cooling channel geometries and routing paths are … derived from the hotspot locations, The claim limitation can be reasonably read to entail evaluating the hotspot locations and using them as a basis for forming a judgment for the cooling channel geometries and routing paths. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim recites this limitation as being performed automatically, thereby indicating the employment of a computer to perform the task. The courts do not distinguish between mental process that may be performed entirely in the human mind or employ the use of generic computers to perform the process.
iteratively refining the conformal cooling arrangement by … that accounts for the cooling channel design to identify any remaining hotspots and further optimize the cooling channel geometries; This claim limitation can be reasonably read to entail evaluating the conformal cooling arrangement and making judgments for ways to improve the arrangement by accounting for the previous deisgn. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. The claim recites the use of an additional predictive thermal model to perform this process which appears to be a generic computing component recited at a high level of generality to perform the process. The courts do not distinguish between mental processes performed entirely in the human mind and those which employ generic computers to execute the process.
determining sensor locations within the mold insert for embedding at least one sensor configured to measure one or more of temperature, pressure, and mold cycle events at the sensor locations; This claim limitation can be reasonably read to entail making a judgment for sensor locations. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Therefore, the claim recites a judicial exception.
Step 2A Prong 2: Additional elements were identified and are noted in italics.
providing a design of an injection mold part;- This limitation has been identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) of mere data gathering.
by a predictive model- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
executing the predictive model simulates thermal behavior of the injection mold part and automatically … the predictive model- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
automatically - This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
automatically - This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
executing an additional predictive thermal model - This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computing components as a tool
forming the mold insert including the conformal cooling arrangement and the at least one embedded sensor within the mold insert, wherein the conformal cooling arrangement comprises cooling channels routed in proximity to the identified hotspots; and- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for amounting to the words “apply it” with regard to the judicial exception. The limitation has also been identified as Field of Use and Technological Environment (MPEP 2106.05(h)) for linking the use of the judicial exception to a particular technological environment.
forming the injection mold part by heating a source of material at the mold insert and cooling the source of material by the conformal cooling arrangement.- This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for amounting to the words “apply it” with regard to the judicial exception.
The courts have found that merely including instructions to implement an abstract idea on a computer or merely using a computer as a tool to perform an abstract idea or reciting the words “apply it” with the judicial exception (Mere Instructions to Apply an Exception (MPEP 2106.05(f))); adding insignificant extra- solution activity to the judicial exception (Insignificant Extra Solution Activity (MPEP 2106.05(g))); and generally linking the use of a judicial exception to a particular technological environment or field of use (Field of Use and Technological Environment (MPEP 2106.05(h))) does not integrate the judicial exception into a practical application.
When viewed independently and within the claim as a whole, the additional element does not appear to integrate the judicial exception into a practical application because the claim does not apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception. The way in which the additional elements interact with the judicial exception(s) appear to be using generic computing components recited at a high level of generality to enable the performance of a task which can be performed in the human mind or using pen and paper as assistive physical aids. Further, the additional elements appear to employ insignificant extra solutionary activity to obtain a design by which to perform the judicial exception on and recite steps of merely applying the judicial exception in a particular technological environment.
Step 2B: As discussed in Step 2A Prong 2, additional elements were identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) which must be further evaluated to determine if they are beyond WURC activities. Additional elements identified otherwise and conclusions from Step 2A Prong 2 are carried over for evaluating if the claim, as a whole, amounts to an inventive concept that is significantly more than the judicial exception:
providing a design of an injection mold part;- This limitation has been identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)) of mere data gathering. Under broadest reasonable interpretation and when read in light of the specification, this additional element entails sending a receiving data over a network. This computer function has been found by the courts to be well understood, routine, and conventional when claimed in a merely generic manner such as in the claim.
The courts have found that simply appending insignificant extra solution activities that are well-understood, routine, and conventional activities to the judicial exception does not qualify the limitations as “significantly more” than the recited judicial exception. The remaining additional elements were identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) and Field of Use and Technological Environment (MPEP 2106.05(h)), as stated previously. The courts have found that merely using a computer as a tool to perform a mental process and generally linking the use of a judicial exception to a particular technological environment does not qualify the limitations as “significantly more” than the recited judicial exception.
With the additional elements viewed independently and as part of the ordered combination, the claim as a whole does not appear to amount to significantly more than the recited judicial exception because the claim is using generic computing components recited at a high level of generality and functioning in their normal capacity in conjunction with well-understood, routine, and conventional activity to enable the performance of a task that can practically be performed within the human mind or using pen and paper as an assistive physical aid. The claim further appears to link the use of the judicial exception to a particular technological environment by reciting additional well-understood, routine, and conventional activities within the art paired with the judicial exception as a mechanism by which to apply the judicial exception in a non-inventive way.
For example, reciting that something is performed “automatically” and/or by a “predictive model” which is not described beyond a high level of generality does not present anything beyond what is well understood, routine and conventional. This is given as evidence by the court’s findings that mere instructions to implement an abstract idea on a computer is not enough to amount to significantly more than the recited judicial exception (MPEP 2106.05(I)(A). The particularity of the machine or apparatus used to implement the design optimization is not specifically identifiable by the claim language such that the claim would demonstrate the use of a particular machine. It is important to note that a general purpose computer that applies a judicial exception, such as an abstract idea, by use of conventional computer functions does not qualify as a particular machine.
Furthermore, applying insert forming process according to the optimized insert design to fabricate the designed insert with conformal cooling channels is not beyond what has been recognized as well understood in the art. Such a process, at least at the level recited by the claim, has been in use since the 1990s, as given by Metal AM (Metal AM, “Conformal cooling: How AM is increasing efficiency and quality in the injection moulding industry”, Sept 1, 2018, metal-am.com), hereinafter referred to as Metal AM which describes its usage dating back to the 1990’s. ((Metal AM, ¶1) "Additive Manufacturing has been used to build moulds incorporating conformal cooling channels since the 1990s when the first metal powder-based AM systems came to market. "). There are no such limitations in the claim that distinguish this process in any inventive capacity beyond what is well known already in the art. While the claim does recite that an embedded sensor occur within the manufactured mold insert, its inclusion, at least based on the claim language, does not demonstrate an improvement to the technology for at least failing to recite in how the sensor is used in any meaningful capacity besides its intended use (temperature, pressure, etc).
Lastly, the claim recites “forming the injection mold part by heating a source of material at the mold insert and cooling the source of material by the conformal cooling arrangement.”. As given by the specification, using mold inserts in injection molding process that heats material to inject into the mold is typical in the art (See at least ¶3-4 of the specification). This evidence further supports that using an insert in an injection molding process in an unspecified way beyond its ordinary capacity is a well understood, routine, and conventional task in the art.
Therefore, the claim does not include additional elements, alone or in combination that are sufficient to amount to significantly more than the recited judicial exception.
Conclusion: Based on this rationale, the claim has been deemed to be ineligible subject matter under 35 U.S.C. 101.
Dependent Claims:
Examiner notes limitations identified as judicial exceptions are indicated in italicized bold and limitations identified as additional elements are indicated using italics.
Claim 2
Step 1: Regarding dependent claim 2, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 2 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 2 additionally recites the limitation embedding the at least one sensor in the mold insert at the one or more sensor locations for providing a feedback loop that modifies a result of the predictive model. This limitation has been identified as the insignificant extra solution activity of data gathering (MPEP 2016.05(g)), Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for amounting to the words “apply it” with regard to the design obtained as part of the judicial exception, and Field of Use and Technological Environment (MPEP 2106.05(h)) for linking the use of the judicial exception to a particular technological environment. The courts have ruled that adding insignificant extra-solution activity to the judicial exception does not integrate the judicial exception into a practical application, nor does stating the words “apply it” with regard for the judicial exception or generally linking the judicial exception to a particular technological environment (MPEP 2106.04(d)) . Note: The limitation “for providing a feedback loop that modifies as result of the predictive model” appears to be a statement of intended use that does not meaningfully limit the claim such that it would be apparent any sensor data collected is used in a meaningful and inventive way.
Step 2B: When read in light of the specification, acquiring data from the sensors is recited at a high level of generality and encompasses receiving data over a network because the specification mentions that sensor data can be sent to a cloud computer. ((¶45) "In some embodiments, one or more sensors are installed in the mold insert for collecting temperature and pressure data at the interface between the mold insert and the injected polymer or metal part."); ((¶56) "In some embodiments, the machine monitoring feature leverages analog sensors, e.g., see FIG. SC, which can be installed at the location of choice on the mold insert. A sensor can collect data to measure temperature as a function of time and/or pressure as a function of time….The data from the analog sensors is the analyzed and sent to a cloud computer or the like where it is processed in a digital format and extrapolated for key elements such as temperatures, pressures, cycle times."); ((¶94) "At block 602, a real-time monitoring process is performed. This may be achieved at block 604, where temperature and pressure data are acquired from one or more sensors 803, for example, shown in FIG. SC."). The courts have recognized the computer function of receiving or transmitting data over a network as well-understood, routine, and conventional activity when claimed in a merely generic manner (MPEP 2106.05(d)(II)(i)). The courts have also found that reciting “apply it” with regard to the judicial exception and generally linking the use of the judicial exception to a particular technological environment does not amount to significantly more. Therefore, the claim does not include additional elements, alone or in combination that are sufficient to amount to significantly more than the recited judicial exception. Further, it appears that the embedding of sensors for in-mold monitoring is a routine practice in the art. This is given as evidence by Ageyeva et al (Ageyeva, T., Horvath, S., and Kovacs, J., “In-Mold Sensors for Injection Molding: On the Way to Industry 4.0”, 2019, Sensors, Vol 19.), hereinafter referred to as Ageyeva which notes that at least two classes of sensors are predominant for in-mold process parameter detection ((Ageyeva, ¶3) "In-mold process parameters are detected by sensors. Different kinds of sensors are available, which vary in measurement purposes and sensing methods. However, for in-mold process control, two classes of sensors are predominant—pressure and temperature sensors."). The fact that there is an identified and prominent class for such application indicates at least a well understood nature of embedding sensors for injection molding monitoring.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 3
Step 1: Regarding dependent claim 3, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 3 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 3 additionally recites the additional element wherein the at least one sensor is configured for at least one of: measuring temperature as a function of time, measuring pressure as a function of time, and identifying an opening and closing of a mold. This limitation has been interpreted as Field of Use and Technological Environment (MPEP 2106.05(h)) because the limitations limit the data used by the abstract idea to the technological environment of instrumenting the injection mold manufacturing process with sensors that capture time-series data. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount to generally linking the use of the judicial exception to a particular technological environment and field of use are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 4
Step 1: Regarding dependent claim 4, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 4 additionally recites the limitation integrating …model data of a first … design of the design with a set of project-specific process parameters or other information; which can reasonably be read to entail associating model data to project-specific process parameters. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. The claim further recites identifying, …, potential improvements to the first … design to generate a second … design; and which can be reasonably read to entail evaluating the first design to make a judgement of potential improvements for the second design. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. And lastly the claim recites comparing, …., the first … design and the second … design to identify possible improvements to the second … design. which can be reasonably read to entail making an evaluation between two designs to make a judgement of possible improvements. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process.
Step 2A Prong 2: Claim 4 additionally recites the limitation computer-aided design (CAD) and CAD throughout the claim, as well as recites performing the judicial exceptions by the predictive model. These limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computers as tools to enable the performance of the mental process. The courts have ruled invoking the use of generic computing components as tools does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount to providing instructions to implement the judicial exception using a generic computer component are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 5
Step 1: Regarding dependent claim 5, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 5 additionally recites the limitation wherein the … is analyzed by … to identify features pertaining to a design of conformal cooling lines of the conformal cooling arrangement within the mold insert. which can reasonably be read to entail evaluating predictive model data to make a judgment on relevant features for a cooling line design. This evaluation can be done within the human mind or using a pen and paper as an assistive physical aid. The limitation includes the usage of an artificial intelligence system, which is a computing component recited at a high level of generality (see instant specification that discusses the AI system can be part of a computer in ¶47). This limitation, as drafted, is a process that, under broadest reasonable interpretation, covers performance of the mind using generic computing components as a tool to perform the concept (MPEP 2106.04(a)(2)(III)(C)) and is thus the recitation of the judicial exception of abstract ideas as a mental process.
Step 2A Prong 2: Claim 5 additionally recites the limitations the predictive model and an artificial intelligence system. These limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of generic computers as tools to enable the performance of the mental process. The courts have ruled invoking the use of generic computing components as tools does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount to providing instructions to implement the judicial exception using a generic computer component are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 6
Step 1: Regarding dependent claim 6, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 6 additionally recites the limitation modifying the design so that the cooling flow geometry and direction from heat dissipation from the hotspots detected in the injection mold part is changed to reduce or eliminate the hotspots. which can reasonably be read to entail evaluating flow geometry and heat dissipation data to inform a judgment on how to modify the design to improve hotspots. This evaluation can be done within the human mind or using a pen and paper as an assistive physical aid. Thus, this limitation includes recitation of the judicial exception of abstract ideas as a mental process
Step 2A Prong 2 & Step 2B: Claim 6 does not include any additional elements that would integrate the judicial exception into a practical application nor amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 7
Step 1: Regarding dependent claim 7, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 7 does not recite any additional judicial exceptions.
Step 2A Prong 2: Claim 7 recites additional element wherein the hotspots are digital representations of the injection mold part, and are emulated in response to analyzing, by the predictive model, the design. This limitation has been interpreted as Field of Use and Technological Environment (MPEP 2106.05(h)) and Mere Instructions to Apply an Exception (MPEP 2106.05(f)) . The limitation links the judicial exception to the technological environment of injection molding manufacturing and process modeling and invokes the use of generic computing components (digital representations, emulation). The courts have ruled that generally linking the use of a judicial exception to a particular technological environment or field of use does not integrate the judicial exception into a practical application (MPEP 2106.04(d)). With the additional elements viewed as part of the ordered combination, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount to generally linking the use of the judicial exception to a particular technological environment and field of use or using computers as a tool by which to apply the judicial exception are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 9
Step 1: Regarding dependent claim 9, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 9 additionally recites the limitation to calculate data metrics in response to forming the injection mold part from the formed mold insert; and, which can reasonably be read to entail calculating data metrics. This task can be performed within the human mind or using a pen and paper as an assistive physical aid. Therefore, this claim limitation includes the recitation of the judicial exception of abstract ideas of a mental process. Furthermore, the recitation of a calculation is additionally the recitation of judicial exceptions of mathematical concepts.
Step 2A Prong 2: Claim 9 additionally recites the limitation executing an artificial intelligence process. This limitation has been identified as Mere Instructions to Apply an Exception (MPEP 2106.05(f)) for invoking the use of a computer to apply the judicial exception. The claim further recites inputting the data metrics to the predictive model. This has been identified as Insignificant Extra Solution Activity (MPEP 2106.05(g)). The courts have ruled appending insignificant extra solution activity to the judicial exception and invoking the use of computers as a tool to apply the judicial exception does not integrate the judicial exception into a practical application. With the additional element viewed in conjunction with the other limitations, the claim as a whole does not appear to integrate the judicial exception into a practical application.
Step 2B: Because a claim was identified to be Insignificant Extra Solution Activity (MPEP 2106.05(g)), it requires further evaluation to determine if the activity is beyond well understood routine and conventional activity. When read in light of the specification, inputting data into the predictive model is recited at a high level of generality and can be executed in the networking elements of Figure 1 (¶72 and Fig 3 item 334) and ((¶57) "FIG. 3 is a flow diagram of a part production process 300 for an injection molding operation, in accordance with some embodiments. In describing the part production process 300, reference may be made to some or all elements of the system 10 of FIG. 1."). Therefore, under broadest reasonable interpretation, this claim limitation encompasses receiving data over a network. The courts have recognized the computer function of receiving or transmitting data over a network as well-understood, routine, and conventional activity when claimed in a merely generic manner. The courts have further found that including mere instructions to apply the judicial exception on a generic computing component are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 10
Step 1: Regarding dependent claim 10, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 10 additionally recites the limitation performing a part selection process including determining a part volume to surface area ratio; and, which can reasonably be read to entail evaluating parameters to select a part and calculating a part volume to surface are ratio. This evaluation can be done within the human mind or using a pen and paper as an assistive physical aid and is thus the recitation of a mental process. The determination of the part volume to surface ratio includes the recitation of mathematical concepts (Step 2A Prong 1). Claim 10 additionally recites the limitation modifying the design of the injection mold part in response to the part volume to surface area ratio exceeding a predetermined threshold. which can reasonably be read to entail evaluating the ratio with respect to a threshold value and further making a judgment on how to modify the design of the injection mold part based on the evaluated ratio. This evaluation can be done within the human mind or using a pen and paper as an assistive physical aid and is thus the recitation of a mental process. The evaluation of the ratio with respect to the threshold includes the recitation of mathematical concepts
Step 2A Prong 2 & Step 2B: Claim 10 does not include any additional elements that would integrate the judicial exception into a practical application nor amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 11
Step 1: Regarding dependent claim 11, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 11 additionally recites the limitation collecting data on time savings estimates due to the conformal cooling arrangement; and, which can reasonably be read to entail evaluating the data points of conformal cooling arrangement to calculate values pertaining to savings estimates. When read in light of the specification, this data can be calculated using Eq. 1 in ¶60. This evaluation can be done within the human mind or using a pen and paper as an assistive physical aid and is thus the recitation of a mental process. The calculation to acquire the data on time savings estimates includes the recitation of mathematical concepts (Step 2A Prong 1). Claim 11 additionally recites the limitation generating a financial invoice from the collected data which can reasonably be read to entail evaluating collected data to produce a financial invoice that reflects the collected data. This evaluation can be done within the human mind or using a pen and paper as an assistive physical aid and is thus the recitation of a mental process. When read in light of the specification, ¶103 states that the invoice “can include a cost that equals a sum of the time saved multiplied by the rate for each part”. Therefore, this claim limitation is the additional recitation of a mathematical concept.
Step 2A Prong 2: Claim 1 additionally recites the limitation performing a machine operation on the mold insert. This limitation has been identified This limitation has been interpreted as Field of Use and Technological Environment (MPEP 2106.05(h)). The limitation links the judicial exception to the technological environment of injection molding manufacturing. The courts have ruled that generally linking the use of a judicial exception to a particular technological environment or field of use does not integrate the judicial exception into a practical application.
Step 2B: The courts have found that limitations that amount generally linking the use of the judicial exception to a particular technological environment are not enough to qualify the claim as significantly more than the abstract idea. Therefore, the claim does not include additional elements, alone or in the ordered combination that are sufficient to amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 12
Step 1: Regarding dependent claim 12, the judicial exception of independent claim 1 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Step 2A Prong 1: Claim 12 additionally recites limitations generating post-processing manufacturing plan from the mold insert to form a final plastic injection mold insert which can reasonably be read to entail evaluating the mold insert in order to inform a subsequent judgment on creating a plan that defines the manufacturing requirements for a final plastic injection mold insert. When read in light of the specification ¶107, the manufacturing plan can include details such as CNC machining, wire cut, electric discharge machining, threading, and sensor locations; and these details can be evaluated within the human mind to make judgements to inform the creation of a manufacturing plan. Thus, this limitation includes recitation of the judicial exception of abstract ideas as a mental process.
Step 2A Prong 2 & Step 2B: Claim 12 does not include any additional elements that would integrate the judicial exception into a practical application nor amount to significantly more than the recited judicial exception.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 14
Step 1: Regarding dependent claim 14, the judicial exception of independent claim 13 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Claim 14 additionally recites limitations that are substantially similar to those recited in claim 2. Therefore, claim 14 is rejected under the same rationale stated previously for the analysis of claim 2.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 15
Step 1: Regarding dependent claim 15, the judicial exception of independent claim 13 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Claim 15 additionally recites limitations that are substantially similar to those recited in claim 4. Therefore, claim 15 is rejected under the same rationale stated previously for the analysis of claim 4.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 16
Step 1: Regarding dependent claim 16, the judicial exception of independent claim 13 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Claim 16 additionally recites limitations that are substantially similar to those recited in claim 5. Therefore, claim 16 is rejected under the same rationale stated previously for the analysis of claim 5.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 17
Step 1: Regarding dependent claim 17, the judicial exception of independent claim 13 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Claim 17 additionally recites limitations that are substantially similar to those recited in claim 6. Therefore, claim 17 is rejected under the same rationale stated previously for the analysis of claim 6.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim 19
Step 1: Regarding dependent claim 19, the judicial exception of independent claim 13 is further incorporated. The claim falls within the corresponding statutory category as stated previously.
Claim 19 additionally recites limitations that are substantially similar to those recited in claim 10. Therefore, claim 19 is rejected under the same rationale stated previously for the analysis of claim 10.
This claim is not eligible subject matter under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 4, 5, 11, 12, 13, 15, 16, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Patel et al (DK 201870126 A1), hereinafter referred to as Patel, in view of Park et al (Park, H., Dang, X., “Development of a smart plastic injection mold with conformal cooling channels”, 2017, Procedia Manufacturing, pp 48-59), hereinafter referred to as Park.
Regarding claim 1, Patel discloses (except the limitations surrounded by brackets ([[..]])) A method of forming a mold insert for an injection molding operation, comprising: ((Patel, Page 16, Lines 33-35) "FIG. 3 schematically illustrates a flow diagram of an embodiment of a method for manufacturing a mold insert, e.g. a method performed by the mold insert optimizing module 110 of FIG. 1.")
providing a design of an injection mold part; ((Patel, Page 14, Lines 1-3) " In particular, the CAD modelling module allows a user to create a CAD model of the part to be injection molded and for which an optimized mold insert is to be created.");((Patel, Page 15, Lines 25-28) "In particular, the optimizer engine may compare the model of the molded part which results from the simulation with the originally received CAD model of the part to be injection molded so as to estimate the tolerances."); ((Patel, Page 17, Lines 1-3) "In initial step S31, the process receives a specification of the part to be injection molded. The specification includes a CAD model of the part and further information, such as a specific choice of material from which the part is to be molded.")
analyzing, by a predictive model, the design to determine a conformal cooling
arrangement for a mold insert for forming the injection mold part; The part is analyzed in a simulation and the process is used to determine the structural influence on the insert ((Patel, Page 17, Lines 36-37 -Page 18, Lines 1-6) "In step S36, the process simulates the injection molding process of the specified part. This step is based on the part specification received in step S31, on the model of the mold insert created in step S34 and on molding process parameters 334. This step results in a digital model (e.g. a volume model or a CAD model) of the injection molded part. In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert. Moreover, during this step the process may determine the structural influence on the insert (e.g. deflections) and feed
relevant data back into the loop, e.g. to be used in a subsequent iteration of step S34. "). The evaluation in the step (S36) is used to modify the mold insert design (S39), as shown in the flowchart of Figure 3. Modifying the mold component (insert) may involve changes to the cooling channels ((Patel, Page 7, Lines 13-17) "The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."); ((Patel, Page 1, Line 35- Page 2, Lines 1-2) "Mold inserts have the function of forming the injected material into the desired shape. They contain important features such the shape-giving geometry, element cavities and cooling channel systems."). The mold component (insert) comprises the arrangement of cooling channels and gates within a conformal mold cavity, thereby indicating a conformal cooling arrangement ((Patel, Page 5, Lines 16-20) "The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels."). The simulator is described as a predictive model ((Patel, Page 16, Lines 3-6) "Generally, the injection molding simulator is configured to model and predict the performance and dynamics of the mold insert in combination with an injection molding equipment as it injects a particular material into a particular mold cavity.").
executing the predictive model to simulate thermal behavior of the injection
mold part ((Patel, Page 17, Lines 24-31) "In step S35, the process performs a virtual inspection of the manufactured mold insert based on the digital model resulting from step S34. The virtual inspection may be done by comparing the digital model with predetermined specifications 332. For example, this step may include a structural/mechanical simulation of the mold insert, e.g. using existing simulation tools such as the Ansys system by Ansys, Inc. or the the Abaqus system from Dassault Systeme. Alternatively or additionally, this step may include a thermal simulation for simulating distortions during an additive manufacturing process, e.g. using the above tools."); and automatically identify hotspots, Hotspots are identified in the step S35 as given above ((Patel, Page 18, Lines 3-4) "In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert.") the hotspots comprising regions of the injection mold part exhibiting a thermal mass and cooling duration that the predictive model identifies as exceeding a baseline thermal behavior of the injection mold part; Simulated attributes of the part are compared, by the process, to predetermined goals/targets and determined whether the results correspondingly fulfill the goals/targets ((Patel, Page 18, Lines 7-22) "In step S37, the process compares the model of the injection molded part resulting from step S36 with the model of the part received in step S31, so as to determine the manufacturing tolerances of the simulated process. In this verification step the CAD model of the part resulting from step S36 is compared to the original CAD model as specified by the designer (e.g. geometric tolerances, etc). In general, deviations between the CAD model of the part produced in the present simulation loop and that of the CAD model produced by the designer can be used as a machine learning input to make sure that each subsequent simulation loop gets closer and closer to the specifications, such that the data can be prepared for physical manufacturing. The process may further evaluate alternative or additional attributes of the simulated process, such as a cycle time of the injection molding process. The process compares the simulated attributes with predetermined goals/targets 335. If the results of the simulated injection molding process fulfill the goals/targets, the process outputs the current mold insert model (and optionally optimized process parameters) for use by a manufacturing process S38 for physically manufacturing the mold insert."); (( Patel, Page 20, Lines 25-30) "comparing the determined tolerances with one or more target tolerances; and, if the determined tolerances are larger than the one or more target tolerances; automatically creating a modified three-dimensional digital model of the mold component and selecting the modified three-dimensional digital model of the mold component as the current three-dimensional digital model of the mold component;"). Tolerances may depend on process parameters ((Patel,, Page 6, Lines 20-24) "However, as the cycle time, the life-time of the
mold component, the cost of the mold component, and/or the tolerances of the molded
part may depend on some of these parameters, in some embodiments, at least some of
these parameters may be varied during the optimization process, e.g. responsive to a
comparison with respective target values and/or based on a computed cost function."). The process parameters include a cooling schedule (as a cooling duration) ((Patel, Page 6, Lines 1-4) "Examples of the molding process parameters may include one or more of the following - A cooling schedule for cooling the molded part, e.g. as defined by the temperature and flow of coolant through the cooling channels of the mold insert and/or other component of the mold;"). The cooling process is modeled with consideration for at least the heat capacity by which the thermal mass can be obtained ((Patel, Page 4, Lines 30-34) "As for the filling process, the equations for modelling the cooling process depend on material properties of the material from which the part is to be molded, such as viscosity, heat conductivity, heat capacity, coefficients of thermal expansion, elasticity, etc. and on process conditions, such as temperature, pressure, etc"). The cycle time of the injection molding process is used as a design criteria, wherein the cycle time is highly dependent upon the cooling time of the of material, thereby indicating that the cycle time would be indicative of a baseline thermal behavior ((Patel, Page 8, Lines 10-13) "In some embodiments, the iterative optimization process seeks to optimize one or more of the following alternative or additional parameters: - Lifetime of the mold component (number of shots); - cycle time of injection molding process."); ((Patel, Page 8, Lines 16-18) "For example, the cycle time may be a direct result of the simulation process, e.g. as the accumulated time for the simulated filling, cooling and ejection processes."); ((Patel, Page 9, Lines 3-6) "The process may comprise repeating the computer-implemented optimization process so as to provide multiple alternative three-dimensional representations of a mold component, e.g. multiple alternatives fulfilling a number of design criteria (e.g. within boundary conditions defining target tolerances, cycle times, etc.).")
determining the conformal cooling arrangement based on the identified hotspots, Hotspots are described as being identified in at least steps S34 and S35. ((Patel, Page 18, Lines 3-4) "In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert.") When following the flowchart given in Fig. 3, the mold insert design modifications (See S39) is dependent upon such steps, thereby indicating that the cooling arrangement is determined based on the identified hotspots. The cooling arrangement may be conformal in nature, as discussed previously ((Patel, Page 5, Lines 16-20) "The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels.").
wherein cooling channel geometries and routing paths are automatically derived from the hotspot locations; The methodology in the flowchart depicted in Figure 3 is described as being performed by the mold insert optimizing module, wherein the mold insert optimization module is further described as being implemented by a programmed computer or software application, thereby indicating that this step is performed automatically ((Patel, page 13, Lines 23-30) "The data processing system 100 may be implemented by a suitably programmed computer or other computing infrastructure implementing a mold insert optimization module 110, a CAD modelling module 104, a database 105 for storing molding process parameters, a database 106 for storing mold insert manufacturing process parameters, a user interface module 103 and a model output module 102. The various modules may be implemented as respective software applications executed by the data processing system. It will be appreciated that some or all of the modules may be combined into a single software application."). Changes to the mold component include cooling channel geometry changes ((Patel, Page 7, Lines 13-17) "The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."). Design features of the insert also include the position (route path) and geometry of the cooling channels ((Patel, page 4, Lines 34-37) "It will further be appreciated that the cooling process depends on a number of features of the mold insert and/or other mold component, such as the cavity geometry, the material of the mold insert and/or other mold component, the number, positions and geometry of cooling channels, etc.")
automatically iteratively refining the conformal cooling arrangement by executing an additional predictive thermal model that accounts for the cooling channel design to identify any remaining hotspots and further optimize the cooling channel geometries; The process is depicted as occurring in an iterative loop to modify the mold insert design, wherein the loop considers an insert manufacturing simulation (S34), a virtual inspection step (S35), an injection molding simulation (S36), (as additional predictive models which may include thermal/cooling analysis and simulation), wherein the steps account for the modified mold insert design. (See Figure 3). The process steps identify hotspots and optimize mold insert designs comprising cooling channel geometries, as stated in the rejection of the limitations above. The process is performed as a computer-implemented process, thereby indicating automatic execution ((Patel, Page 11, Lines 13-35) "performing a computer-implemented optimization process for modifying the current three-dimensional digital model of the mold component, the optimization process comprising: a) performing a computer-implemented simulation of an injection molding process for injection molding the part using a mold component manufactured based on the current three-dimensional model of the mold component, the computer-implemented simulation process receiving the received values of the one or more molding process parameters and the received three-dimensional digital model of the part; the computer-implemented simulation process resulting in a three-dimensional model of an injection molded part; b) comparing the three-dimensional model of an injection molded part with the received three-dimensional digital model of the part to be injection molded to determine one or more tolerances of the injection model part; c) comparing the determined tolerances with one or more target tolerances; and, if the determined tolerances are larger than the one or more target tolerances; automatically creating a modified three-dimensional digital model of the mold component and selecting the modified three-dimensional digital model of the mold component as the current three-dimensional digital model of the mold component; d) repeating steps a) through c) until the determined tolerances are no larger than the one or more target tolerances.")
[[determining sensor locations within the mold insert for embedding at least one sensor configured to measure one or more of temperature, pressure, and mold cycle events at the sensor locations;]]
manufacturing the mold insert by adding material one layer at a time to form the conformal cooling arrangement [[and the at least one embedded sensor within a metal structure of the mold insert,]] wherein the conformal cooling arrangement comprises cooling channels routed in proximity to the identified hotspots; The mold component, which may be an insert, may be manufactured according to an additive process, wherein an additive process is understood to add material in incremental layers ((Patel, Page 9 Lines 20-23) "The manufacturing of the mold component may be performed in a variety of ways, dependent on the resulting choice of material from which the mold component is manufactured and the resulting geometry. Suitable manufacturing methods may include additive manufacturing such as 3D printing, molding, machining etc."); ((Patel, Page 18, Lines 31-34) "For example, while the above embodiments have mainly been described with reference to a mold insert, it will be appreciated that other embodiments may be used to design and manufacture other mold components."). The mold component design model used in the manufacturing (See Fig 3, S38 receiving the optimized mold insert design for manufacture) includes the arrangement of cooling channels ((Patel, Page 5, Lines 16-20, ¶) "The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels."); ((Patel, Pages 7, Lines 13-17) "The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."). Hotspots are observed in the insert, in steps S34 and S35 as given above ((Patel, Page 18, Lines 3-4) "In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert."). Because the hotspots are identified in the insert and the cooling channels are part of the insert, the cooling channels are clearly routed in some proximity to any identified hotspot, at least by association of both occurring in the same component.
using the mold insert in an injection molding process to form the injection mold
part. ((Patel, Page 1, Lines 7-18) "Injection molding is a widely used manufacturing process for producing parts by injecting material into a mold. Injection molding can be performed with a host of materials including elastomers, thermoplastic and thermosetting polymers. Typical injection molding processes involve heating and melting the material, injecting the melted material into a mold cavity, allowing the injected material to cool and harden to the configuration of the cavity and ejecting the hardened part. Traditionally, once the part to be molded has been designed, usually by an industrial designer or an engineer, a tool maker has designed and precision machined a suitable mold from metal, such as steel or aluminium, so as to form the features of the designed part. The initial design and manufacture of the mold using traditional mold insert
manufacturing techniques is quite costly. Once a mold is manufactured it can be used, in some instances, to manufacture millions of parts"); ((Patel, page 8, Lines 18-19) "Accordingly, the process may provide a more efficient manufacturing process (e.g. by optimizing for the cycle time of the injection molding process).")
Patel alone does not explicitly disclose or appear to contemplate the determination of sensor locations for embedding sensors within a mold insert, nor does Patel explicitly disclose that the mold insert comprise a metal structure. However; Park discloses
determining sensor locations within the mold insert for embedding at least one sensor configured to measure one or more of temperature, pressure, and mold cycle events at the sensor locations; Sensors are placed at identified positions in the injection mold insert, wherein the sensors have corresponding holes by which to be integrated into the assembly as depicted in Figure 6.
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Sensors are described as being a temperature sensor and a pressure sensor ((Park, Page 54, ¶1) "There is also a constraint that the new cooling system is not allowed to interfere with ejection system, temperature sensor and pressure sensor")
and the at least one embedded sensor within a metal structure of the mold insert, The sensors are shown in Figure 6 as being placed in the cooling channels. The cooling channels are described s being manufactured via metal 3D printing technology ((Park, Page 49, ¶3) " Because of the advancement in metal 3D printing technology, the application of conformal cooling channels made by solid freeform fabrication is becoming popular recently. The conformal cooling channels system is recognized as one of the best solutions in reducing cycle time, differential shrinkage, and warpage defects on molded parts [6]. Although conformal cooling channels applied to injection mold is no longer new, the design and optimization of conformal cooling channels for special practical application is still a research problem. Ahn D.G et al. [7] studied on the manufacture of an injection mold for plastic fan with a pair of conformal cooling channels in each blade via laser-aided direct metal tooling process to achieve both rapid and uniform cooling characteristics"); ((Park, Page 48, ¶Abstract) "To cool the positions with thicker walls, we proposed local conformal cooling channels in which the cooling lines are in the spiral form. The mold was designed with special inserts. Selective laser melting (SLM) 3D printing has been used to make the inserts with conformal cooling channels inside. In the first phase of the development process, the research results show that conformal cooling channels reduce the cycle time approximately 30% compared to conventional cooling channels"); ((Park, Page 57, ¶2) "After design and simulation, we decided to make the inserts. The two inserts were fabricated by selective laser melting method on MetalSys 150 3D printer with P21 material. The printing process and the result of one insert are shown in Figure 11a.")
Patel is analogous to the claimed invention because it is related to the same field of endeavor of optimizing cooling channel design in inserts for injection molding applications. Park is likewise analogous to the claimed invention because it pertains to the same field of endeavor of optimizing cooling channel design for injection molding applications. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have modified the disclosure of Patel to incorporate the teachings of Park because some teaching, suggestion, or motivation would have led one having ordinary skill to do so in order to arrive at the claimed invention. Park suggests that incorporating sensors into an injection molding insert may be beneficial for monitoring important locations of the mold so as to employ intelligent molding control. Park additionally demonstrates that using SLM additive manufacturing to make the inserts with conformal cooling channels inside results in rapid manufacturing for freeform-type designs. Accordingly, one having skill in the art would be motivated to incorporate such features to further enhance the teachings of Patel.
Regarding claim 4, the proposed combination discloses The method of claim 1, wherein analyzing, by the predictive model, the design includes: as stated previously.
The proposed combination in further view of Patel discloses integrating computer-aided design (CAD) model data of a first CAD design of the design with a set of project-specific process parameters or other information; The optimizer engine uses a CAD design from the CAD modeling module in conjunction with process parameters for a simulation. ((Patel, Page 15, Lines 3-10) " The optimizer engine 111 defines the initial values of the input parameters for the simulation, initiates the simulators 112 and 115, respectively, evaluates the results of the simulations, adjusts the simulations parameters based on the evaluation, and iterates the simulation with adjusted parameters until the result of the simulations fulfill predetermined criteria. In particular, the optimizer engine 111 defines an initial model of the mold insert, e.g. as received from the CAD modeling module 104, and initial values of the process parameters, e.g. based on user input and/or from data stored in databases 105 and 106.")
identifying, by the predictive model, potential improvements to the first CAD design to generate a second CAD design; and The optimizer engine performs an iterative process where process parameters and the mold insert model may be modified to optimize one or more other parameters (identified improvements). The simulation produces a final optimized model of the manufactured mold insert, indicating that at least a second CAD design is generated. ((Patel, Page 15, lines 11-17) " The optimizer engine 111 initially executes the simulator 112 to perform a simulation of the mold insert manufacturing process based on the received CAD model of the mold insert and the associated mold insert manufacturing process parameters. The simulation of the mold insert manufacturing process results in a model of the manufactured mold insert. It will be appreciated that the simulation process may be an iterative process where various process parameters and/or the mold insert model may iteratively be modified so as to optimize for one or more parameters, such as production cost, etc.").
comparing, by the predictive model, the first CAD design and the second CAD design to identify possible improvements to the second CAD design. The originally received design is compared to the model of the molded part that is produced by the predictive simulation. Tolerances are evaluated to identify possible improvements of the model design generated from the simulation. ((Patel, Page 15, lines 18-32) " Subsequently, the optimizer engine executes simulator 115 to perform a simulation of the injection molding process based on the mold insert model created by the simulator 112 and from associated molding parameters, such as choice of material, temperature, pressure, etc. The simulation of the injection molding process results in a model of the injection molded part. It will be appreciated that the simulation process may be an iterative process where various process parameters and/or the mold insert model may iteratively be modified so as to optimize for one or more parameters, such as manufacturing tolerances, cycle time, etc. In particular, the optimizer engine may compare the model of the molded part which results from the simulation with the originally received CAD model of the part to be injection molded so as to estimate the tolerances. If the model of the injection molded part shows that the injection molded part lies outside the target tolerances, the optimizer engine may alter the mold insert model and/or the process parameters and execute simulator 115 again based on the modified model and/or process parameters. The optimizer engine may even execute both simulators 112 and 115 again.")
Regarding claim 5, the proposed combination discloses The method of claim 4, as stated above. The proposed combination further in view of Patel discloses wherein the predictive model is analyzed by an artificial intelligence system to identify features pertaining to a design of conformal cooling lines of the conformal cooling arrangement within the mold insert. The optimization process employs machine learning to take as input CAD models developed as part of the optimization process to improve subsequent simulations, wherein the process may include the evaluation of attributes of the simulated process (features pertaining to design), wherein the simulation has been described as a component of the design of the mold insert containing conformal cooling lines ((Patel, Page 18, Lines 11-18) " In general, deviations between the CAD model of the part produced in the present simulation loop and that of the CAD model produced by the designer can be used as a machine learning input to make sure that each subsequent simulation loop gets closer and closer to the specifications, such that the data can be prepared for physical manufacturing. The process may further evaluate alternative or additional attributes of the simulated process, such as a cycle time of the injection molding process. The process compares the simulated attributes with predetermined goals/targets 335."); ((Patel, page 5, Lines 16-20) " The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels."); ((Patel, Page 1, Lines 21-24) " Examples of design features of an injection mold that influence the quality of the resulting part include that arrangement of gates though which the molten material is injected into the cavity, the arrangement of cooling channels through which coolant is passed so as to cool the injected material, the location of the parting lines, etc.")
Regarding claim 11, the proposed combination discloses The method of claim 1, further comprising: as stated previously.
The proposed combination in further view of Patel discloses performing a machine operation on the mold insert; The mold insert may be manufactured via different types of machinery ((Patel, Page 9, ¶20-26) " The manufacturing of the mold component may be performed in a variety of ways, dependent on the resulting choice of material from which the mold component is manufactured and the resulting geometry. Suitable manufacturing methods may include additive manufacturing such as 3D printing, molding, machining etc. Dependent upon the manufacturing method (e.g. additive manufacturing), the mold component may be made from a single material or from multiple materials. For example, different parts of the mold component may be made from different materials.")
collecting data on time savings estimates due to the conformal cooling arrangement; and Production and cycle time may be optimized for the injection molding process based on the mold insert model, indicating collecting data on time saving per the cooling configuration ((Patel, Page 15 Lines 15-25) " It will be appreciated that the simulation process may be an iterative process where various process parameters and/or the mold insert model may iteratively be modified so as to optimize for one or more parameters, such as production cost, etc. Subsequently, the optimizer engine executes simulator 115 to perform a simulation of the injection molding process based on the mold insert model created by the simulator 112 and from associated molding parameters, such as choice of material, temperature, pressure, etc. The simulation of the injection molding process results in a model of the injection molded part. It will be appreciated that the simulation process may be an iterative process where various process parameters and/or the mold insert model may iteratively be modified so as to optimize for one or more parameters, such as manufacturing tolerances, cycle time, etc."). The mold insert model may comprise conformal cooling channel arrangement that may be optimized as part of the process ((Patel, Page 5, Lines 16-20) " The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels."); ((Patel, Page 7, Lines 13-17) " The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."); ((Patel, Page 8, Lines 31-34 – Page 9, Lines 1-2) " Regarding shrinkage compensation, embodiments of the optimization process may implement a prioritization of what features to change. The purpose of prioritization would be to avoid over-engineering what could be done with a simpler method - cavity shape – leverage multimaterial/HOD to optimize for heat conduction to influence shrinkage, conformal cooling channels, etc.")
generating a financial invoice from the collected data. The database stores information about the mold insert manufacturing process, including cost((Patel, Page 14, Lines 15-20) " The database 106 has stored therein information about the mold insert manufacturing process, including material properties and process conditions. The material properties include physical parameters such as specific density, heat conductivity, elasticity, etc. and other material-specific parameters, such as cost, typical lifetime, available material-specific manufacturing processes, etc. of various materials used for manufacturing the mold insert."); ((Patel, Page 15, Lines 15-17) " It will be appreciated that the simulation process may be an iterative process where various process parameters and/or the mold insert model may iteratively be modified so as to optimize for one or more parameters, such as production cost, etc.")
Regarding claim 12, the proposed combination discloses The method of claim 1, further comprising: as stated previously.
The proposed combination in further view of Patel discloses generating post-processing manufacturing plan from the mold insert to form a final plastic injection mold insert. Figure 3 shows a mold insert manufacturing step, indicating a plan by which to manufacture the mold insert. Furthermore, an external mold manufacturing system utilizes an optimized CAD model to manufacture the insert. The CAD design is the basis of the manufacturing plan for the mold insert. ((Patel, Page 14, Lines 32-36) " The model output module 102 is configured to provide a CAD model of the optimized mold insert for use by an external mold manufacturing system 170. The model output module 102 may comprise a suitable data storage for storing the CAD model and/or a data communications interface for communicating a CAD model to another system, e.g. via a computer network."). The injection process that leverages the mold insert may use polymer material, thereby indicating that the injection mold will be used for plastic injection ((Patel, Page 14, Lines 9-11) " The material properties include parameters such as viscosity, heat conductivity, etc. of various materials used for injection molding the parts, such as for various elastomers, thermoplastic and thermosetting polymers.")
Regarding claim 13, Patel discloses (except the limitations surrounded by brackets ([[..]])) A method for molding a part of interest, comprising: ((Patel, Page 2, Lines 17-18) "Disclosed herein are embodiments of a method for manufacturing a mold component for injection molding a predetermined part, the method comprising:")
providing a design of an injection mold part; ((Patel, Page 14, Lines 1-3) " In particular, the CAD modelling module allows a user to create a CAD model of the part to be injection molded and for which an optimized mold insert is to be created.");((Patel, Page 15, Lines 25-28) "In particular, the optimizer engine may compare the model of the molded part which results from the simulation with the originally received CAD model of the part to be injection molded so as to estimate the tolerances."); ((Patel, Page 17, Lines 1-3) "In initial step S31, the process receives a specification of the part to be injection molded. The specification includes a CAD model of the part and further information, such as a specific choice of material from which the part is to be molded.")
analyzing, by a predictive model, the design to determine a conformal cooling
arrangement for a mold insert for forming the injection mold part; The part is analyzed in a simulation and the process is used to determine the structural influence on the insert ((Patel, Page 17, Lines 36-37 -Page 18, Lines 1-6) "In step S36, the process simulates the injection molding process of the specified part. This step is based on the part specification received in step S31, on the model of the mold insert created in step S34 and on molding process parameters 334. This step results in a digital model (e.g. a volume model or a CAD model) of the injection molded part. In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert. Moreover, during this step the process may determine the structural influence on the insert (e.g. deflections) and feed
relevant data back into the loop, e.g. to be used in a subsequent iteration of step S34. "). The evaluation in the step (S36) is used to modify the mold insert design (S39), as shown in the flowchart of Figure 3. Modifying the mold component (insert) may involve changes to the cooling channels ((Patel, Page 7, Lines 13-17) "The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."); ((Patel, Page 1, Line 35- Page 2, Lines 1-2) "Mold inserts have the function of forming the injected material into the desired shape. They contain important features such the shape-giving geometry, element cavities and cooling channel systems."). The mold component (insert) comprises the arrangement of cooling channels and gates within a conformal mold cavity, thereby indicating a conformal cooling arrangement ((Patel, Page 5, Lines 16-20) "The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels."). The simulator is described as a predictive model ((Patel, Page 16, Lines 3-6) "Generally, the injection molding simulator is configured to model and predict the performance and dynamics of the mold insert in combination with an injection molding equipment as it injects a particular material into a particular mold cavity.").
executing the predictive model simulates thermal behavior of the injection mold
part ((Patel, Page 17, Lines 24-31) "In step S35, the process performs a virtual inspection of the manufactured mold insert based on the digital model resulting from step S34. The virtual inspection may be done by comparing the digital model with predetermined specifications 332. For example, this step may include a structural/mechanical simulation of the mold insert, e.g. using existing simulation tools such as the Ansys system by Ansys, Inc. or the the Abaqus system from Dassault Systeme. Alternatively or additionally, this step may include a thermal simulation for simulating distortions during an additive manufacturing process, e.g. using the above tools."); and automatically identify hotspots, Hotspots are identified in the step S35 as given above ((Patel, Page 18, Lines 3-4) "In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert.") the hotspots comprising regions of the injection mold part exhibiting a thermal mass and cooling duration that the predictive model identifies as exceeding a baseline thermal behavior of the injection mold part; Simulated attributes of the part are compared, by the process, to predetermined goals/targets and determined whether the results correspondingly fulfill the goals/targets ((Patel, Page 18, Lines 7-22) "In step S37, the process compares the model of the injection molded part resulting from step S36 with the model of the part received in step S31, so as to determine the manufacturing tolerances of the simulated process. In this verification step the CAD model of the part resulting from step S36 is compared to the original CAD model as specified by the designer (e.g. geometric tolerances, etc). In general, deviations between the CAD model of the part produced in the present simulation loop and that of the CAD model produced by the designer can be used as a machine learning input to make sure that each subsequent simulation loop gets closer and closer to the specifications, such that the data can be prepared for physical manufacturing. The process may further evaluate alternative or additional attributes of the simulated process, such as a cycle time of the injection molding process. The process compares the simulated attributes with predetermined goals/targets 335. If the results of the simulated injection molding process fulfill the goals/targets, the process outputs the current mold insert model (and optionally optimized process parameters) for use by a manufacturing process S38 for physically manufacturing the mold insert."); (( Patel, Page 20, Lines 25-30) "comparing the determined tolerances with one or more target tolerances; and, if the determined tolerances are larger than the one or more target tolerances; automatically creating a modified three-dimensional digital model of the mold component and selecting the modified three-dimensional digital model of the mold component as the current three-dimensional digital model of the mold component;"). Tolerances may depend on process parameters ((Patel,, Page 6, Lines 20-24) "However, as the cycle time, the life-time of the
mold component, the cost of the mold component, and/or the tolerances of the molded
part may depend on some of these parameters, in some embodiments, at least some of
these parameters may be varied during the optimization process, e.g. responsive to a
comparison with respective target values and/or based on a computed cost function."). The process parameters include a cooling schedule (as a cooling duration) ((Patel, Page 6, Lines 1-4) "Examples of the molding process parameters may include one or more of the following - A cooling schedule for cooling the molded part, e.g. as defined by the temperature and flow of coolant through the cooling channels of the mold insert and/or other component of the mold;"). The cooling process is modeled with consideration for at least the heat capacity by which the thermal mass can be obtained ((Patel, Page 4, Lines 30-34) "As for the filling process, the equations for modelling the cooling process depend on material properties of the material from which the part is to be molded, such as viscosity, heat conductivity, heat capacity, coefficients of thermal expansion, elasticity, etc. and on process conditions, such as temperature, pressure, etc"). The cycle time of the injection molding process is used as a design criteria, wherein the cycle time is highly dependent upon the cooling time of the of material, thereby indicating that the cycle time would be indicative of a baseline thermal behavior ((Patel, Page 8, Lines 10-13) "In some embodiments, the iterative optimization process seeks to optimize one or more of the following alternative or additional parameters: - Lifetime of the mold component (number of shots); - cycle time of injection molding process."); ((Patel, Page 8, Lines 16-18) "For example, the cycle time may be a direct result of the simulation process, e.g. as the accumulated time for the simulated filling, cooling and ejection processes."); ((Patel, Page 9, Lines 3-6) "The process may comprise repeating the computer-implemented optimization process so as to provide multiple alternative three-dimensional representations of a mold component, e.g. multiple alternatives fulfilling a number of design criteria (e.g. within boundary conditions defining target tolerances, cycle times, etc.).")
determining the conformal cooling arrangement based on the identified hotspots, Hotspots are described as being identified in at least steps S34 and S35. ((Patel, Page 18, Lines 3-4) "In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert.") When following the flowchart given in Fig. 3, the mold insert design modifications (See S39) is dependent upon such steps, thereby indicating that the cooling arrangement is determined based on the identified hotspots. The cooling arrangement may be conformal in nature, as discussed previously ((Patel, Page 5, Lines 16-20) "The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels.").
wherein the cooling channel geometries and routing paths are automatically derived from the hotspot locations; The methodology in the flowchart depicted in Figure 3 is described as being performed by the mold insert optimizing module, wherein the mold insert optimization module is further described as being implemented by a programmed computer or software application, thereby indicating that this step is performed automatically ((Patel, page 13, Lines 23-30) "The data processing system 100 may be implemented by a suitably programmed computer or other computing infrastructure implementing a mold insert optimization module 110, a CAD modelling module 104, a database 105 for storing molding process parameters, a database 106 for storing mold insert manufacturing process parameters, a user interface module 103 and a model output module 102. The various modules may be implemented as respective software applications executed by the data processing system. It will be appreciated that some or all of the modules may be combined into a single software application."). Changes to the mold component include cooling channel geometry changes ((Patel, Page 7, Lines 13-17) "The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."). Design features of the insert also include the position (route path) and geometry of the cooling channels ((Patel, page 4, Lines 34-37) "It will further be appreciated that the cooling process depends on a number of features of the mold insert and/or other mold component, such as the cavity geometry, the material of the mold insert and/or other mold component, the number, positions and geometry of cooling channels, etc.")
automatically iteratively refining the conformal cooling arrangement by executing an additional predictive thermal model that accounts for the cooling channel design to identify any remaining hotspots and further optimize the cooling channel geometries; The process is depicted as occurring in an iterative loop to modify the mold insert design, wherein the loop considers an insert manufacturing simulation (S34), a virtual inspection step (S35), an injection molding simulation (S36), (as additional predictive models which may include thermal/cooling analysis and simulation), wherein the steps account for the modified mold insert design. (See Figure 3). The process steps identify hotspots and optimize mold insert designs comprising cooling channel geometries, as stated in the rejection of the limitations above. The process is performed as a computer-implemented process, thereby indicating automatic execution ((Patel, Page 11, Lines 13-35) "performing a computer-implemented optimization process for modifying the current three-dimensional digital model of the mold component, the optimization process comprising: a) performing a computer-implemented simulation of an injection molding process for injection molding the part using a mold component manufactured based on the current three-dimensional model of the mold component, the computer-implemented simulation process receiving the received values of the one or more molding process parameters and the received three-dimensional digital model of the part; the computer-implemented simulation process resulting in a three-dimensional model of an injection molded part; b) comparing the three-dimensional model of an injection molded part with the received three-dimensional digital model of the part to be injection molded to determine one or more tolerances of the injection model part; c) comparing the determined tolerances with one or more target tolerances; and, if the determined tolerances are larger than the one or more target tolerances; automatically creating a modified three-dimensional digital model of the mold component and selecting the modified three-dimensional digital model of the mold component as the current three-dimensional digital model of the mold component; d) repeating steps a) through c) until the determined tolerances are no larger than the one or more target tolerances.")
[[determining sensor locations within the mold insert for embedding at least one sensor configured to measure one or more of temperature, pressure, and mold cycle events at the sensor locations;]]
forming the mold insert including the conformal cooling arrangement [[and the at least one embedded sensor within the mold insert,]] wherein the conformal cooling arrangement comprises cooling channels routed in proximity to the identified hotspots; and The mold component, which may be an insert, may be manufactured according to an additive process, wherein an additive process is understood to add material in incremental layers ((Patel, Page 9 Lines 20-23) "The manufacturing of the mold component may be performed in a variety of ways, dependent on the resulting choice of material from which the mold component is manufactured and the resulting geometry. Suitable manufacturing methods may include additive manufacturing such as 3D printing, molding, machining etc."); ((Patel, Page 18, Lines 31-34) "For example, while the above embodiments have mainly been described with reference to a mold insert, it will be appreciated that other embodiments may be used to design and manufacture other mold components."). The mold component design model used in the manufacturing (See Fig 3, S38 receiving the optimized mold insert design for manufacture) includes the arrangement of cooling channels ((Patel, Page 5, Lines 16-20, ¶) "The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels."); ((Patel, Pages 7, Lines 13-17) "The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."). Hotspots are observed in the insert, in steps S34 and S35 as given above ((Patel, Page 18, Lines 3-4) "In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert."). Because the hotspots are identified in the insert and the cooling channels are part of the insert, the cooling channels are clearly routed in some proximity to any identified hotspot, at least by association of both occurring in the same component.
forming the injection mold part by heating a source of material at the mold insert
and cooling the source of material by the conformal cooling arrangement..((Patel, Page 1, Lines 7-18) "Injection molding is a widely used manufacturing process for producing parts by injecting material into a mold. Injection molding can be performed with a host of materials including elastomers, thermoplastic and thermosetting polymers. Typical injection molding processes involve heating and melting the material, injecting the melted material into a mold cavity, allowing the injected material to cool and harden to the configuration of the cavity and ejecting the hardened part. Traditionally, once the part to be molded has been designed, usually by an industrial designer or an engineer, a tool maker has designed and precision machined a suitable mold from metal, such as steel or aluminium, so as to form the features of the designed part. The initial design and manufacture of the mold using traditional mold insert
manufacturing techniques is quite costly. Once a mold is manufactured it can be used, in some instances, to manufacture millions of parts"); ((Patel, page 8, Lines 18-19) "Accordingly, the process may provide a more efficient manufacturing process (e.g. by optimizing for the cycle time of the injection molding process)."); ((Patel, Page 1, Lines 21-24) "Examples of design features of an injection mold that influence the quality of the resulting part include that arrangement of gates though which the molten material is injected into the cavity, the arrangement of cooling channels through which coolant is passed so as to cool the injected material, the location of the parting lines, etc.")
Patel alone does not explicitly disclose or appear to contemplate the determination of sensor locations for embedding sensors within a mold insert.. However; Park discloses
determining sensor locations within the mold insert for embedding at least one sensor configured to measure one or more of temperature, pressure, and mold cycle events at the sensor locations; Sensors are placed at identified positions in the injection mold insert, wherein the sensors have corresponding holes by which to be integrated into the assembly as depicted in Figure 6.
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Sensors are described as being a temperature sensor and a pressure sensor ((Park, Page 54, ¶1) "There is also a constraint that the new cooling system is not allowed to interfere with ejection system, temperature sensor and pressure sensor")
and the at least one embedded sensor within the mold insert, The sensors are shown in Figure 6 as being placed in the cooling channels. The cooling channels are described as being manufactured via metal 3D printing technology ((Park, Page 49, ¶3) " Because of the advancement in metal 3D printing technology, the application of conformal cooling channels made by solid freeform fabrication is becoming popular recently. The conformal cooling channels system is recognized as one of the best solutions in reducing cycle time, differential shrinkage, and warpage defects on molded parts [6]. Although conformal cooling channels applied to injection mold is no longer new, the design and optimization of conformal cooling channels for special practical application is still a research problem. Ahn D.G et al. [7] studied on the manufacture of an injection mold for plastic fan with a pair of conformal cooling channels in each blade via laser-aided direct metal tooling process to achieve both rapid and uniform cooling characteristics"); ((Park, Page 57, ¶2) "After design and simulation, we decided to make the inserts. The two inserts were fabricated by selective laser melting method on MetalSys 150 3D printer with P21 material. The printing process and the result of one insert are shown in Figure 11a.")
Patel is analogous to the claimed invention because it is related to the same field of endeavor of optimizing cooling channel design in inserts for injection molding applications. Park is likewise analogous to the claimed invention because it pertains to the same field of endeavor of optimizing cooling channel design for injection molding applications. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have modified the disclosure of Patel to incorporate the teachings of Park because some teaching, suggestion, or motivation would have led one having ordinary skill to do so in order to arrive at the claimed invention. Park suggests that incorporating sensors into an injection molding insert may be beneficial for monitoring important locations of the mold so as to employ intelligent molding control. Accordingly, one having skill in the art would be motivated to incorporate such features to further enhance the teachings of Patel.
Regarding claim 15, the proposed combination discloses The method of claim 13, wherein analyzing, by the predictive model, the design includes: as stated previously.
The proposed combination in further view of Patel discloses limitations that are substantially similar to that recited in claim 4 but with respect to independent claim 13: integrating CAD model data of a first CAD design of the design with a set of project-specific process parameters or other information;
identifying, by the predictive model, potential improvements to the first CAD design to generate a second CAD design;
comparing, by the predictive model, the first CAD design and the second CAD design to identify possible improvements to the second CAD design. The limitations are therefore rejected under the same rationale provided for claim 4 with consideration to claim 13.
Regarding claim 16, the proposed combination discloses The method of claim 15, as stated previously.
The proposed combination in further view of Patel discloses wherein the predictive model is analyzed by an artificial intelligence system to identify features pertaining to a design of conformal cooling lines of the conformal cooling arrangement within the mold insert which are substantially similar limitations to that recited in claim 5 but with respect to claim 15. Claim 16 is therefore rejected under the same rationale as provided for claim 5.
Regarding claim 20, Patel discloses (except the limitations surrounded by brackets ([[..]])) A part formed according to a process comprising steps of: ((Patel, Page 1, Lines 17-18) " Once a mold is manufactured it can be used, in some instances, to manufacture millions of parts.")
providing a design of an injection mold part; ((Patel, Page 14, Lines 1-3) " In particular, the CAD modelling module allows a user to create a CAD model of the part to be injection molded and for which an optimized mold insert is to be created.");((Patel, Page 15, Lines 25-28) "In particular, the optimizer engine may compare the model of the molded part which results from the simulation with the originally received CAD model of the part to be injection molded so as to estimate the tolerances."); ((Patel, Page 17, Lines 1-3) "In initial step S31, the process receives a specification of the part to be injection molded. The specification includes a CAD model of the part and further information, such as a specific choice of material from which the part is to be molded.")
analyzing, by a predictive model, the design to determine a conformal cooling arrangement for a mold insert for forming the injection mold part; The part is analyzed in a simulation and the process is used to determine the structural influence on the insert ((Patel, Page 17, Lines 36-37 -Page 18, Lines 1-6) "In step S36, the process simulates the injection molding process of the specified part. This step is based on the part specification received in step S31, on the model of the mold insert created in step S34 and on molding process parameters 334. This step results in a digital model (e.g. a volume model or a CAD model) of the injection molded part. In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert. Moreover, during this step the process may determine the structural influence on the insert (e.g. deflections) and feed
relevant data back into the loop, e.g. to be used in a subsequent iteration of step S34. "). The evaluation in the step (S36) is used to modify the mold insert design (S39), as shown in the flowchart of Figure 3. Modifying the mold component (insert) may involve changes to the cooling channels ((Patel, Page 7, Lines 13-17) "The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."); ((Patel, Page 1, Line 35- Page 2, Lines 1-2) "Mold inserts have the function of forming the injected material into the desired shape. They contain important features such the shape-giving geometry, element cavities and cooling channel systems."). The mold component (insert) comprises the arrangement of cooling channels and gates within a conformal mold cavity, thereby indicating a conformal cooling arrangement ((Patel, Page 5, Lines 16-20) "The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels."). The simulator is described as a predictive model ((Patel, Page 16, Lines 3-6) "Generally, the injection molding simulator is configured to model and predict the performance and dynamics of the mold insert in combination with an injection molding equipment as it injects a particular material into a particular mold cavity.").
executing the predictive model to simulate thermal behavior of the injection mold part ((Patel, Page 17, Lines 24-31) "In step S35, the process performs a virtual inspection of the manufactured mold insert based on the digital model resulting from step S34. The virtual inspection may be done by comparing the digital model with predetermined specifications 332. For example, this step may include a structural/mechanical simulation of the mold insert, e.g. using existing simulation tools such as the Ansys system by Ansys, Inc. or the the Abaqus system from Dassault Systeme. Alternatively or additionally, this step may include a thermal simulation for simulating distortions during an additive manufacturing process, e.g. using the above tools."); and automatically identify hotspots, Hotspots are identified in the step S35 as given above ((Patel, Page 18, Lines 3-4) "In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert.") the hotspots comprising regions of the injection mold part exhibiting a thermal mass and cooling duration that the predictive model identifies as exceeding a baseline thermal behavior of the injection mold part; Simulated attributes of the part are compared, by the process, to predetermined goals/targets and determined whether the results correspondingly fulfill the goals/targets ((Patel, Page 18, Lines 7-22) "In step S37, the process compares the model of the injection molded part resulting from step S36 with the model of the part received in step S31, so as to determine the manufacturing tolerances of the simulated process. In this verification step the CAD model of the part resulting from step S36 is compared to the original CAD model as specified by the designer (e.g. geometric tolerances, etc). In general, deviations between the CAD model of the part produced in the present simulation loop and that of the CAD model produced by the designer can be used as a machine learning input to make sure that each subsequent simulation loop gets closer and closer to the specifications, such that the data can be prepared for physical manufacturing. The process may further evaluate alternative or additional attributes of the simulated process, such as a cycle time of the injection molding process. The process compares the simulated attributes with predetermined goals/targets 335. If the results of the simulated injection molding process fulfill the goals/targets, the process outputs the current mold insert model (and optionally optimized process parameters) for use by a manufacturing process S38 for physically manufacturing the mold insert."); (( Patel, Page 20, Lines 25-30) "comparing the determined tolerances with one or more target tolerances; and, if the determined tolerances are larger than the one or more target tolerances; automatically creating a modified three-dimensional digital model of the mold component and selecting the modified three-dimensional digital model of the mold component as the current three-dimensional digital model of the mold component;"). Tolerances may depend on process parameters ((Patel,, Page 6, Lines 20-24) "However, as the cycle time, the life-time of the
mold component, the cost of the mold component, and/or the tolerances of the molded
part may depend on some of these parameters, in some embodiments, at least some of
these parameters may be varied during the optimization process, e.g. responsive to a
comparison with respective target values and/or based on a computed cost function."). The process parameters include a cooling schedule (as a cooling duration) ((Patel, Page 6, Lines 1-4) "Examples of the molding process parameters may include one or more of the following - A cooling schedule for cooling the molded part, e.g. as defined by the temperature and flow of coolant through the cooling channels of the mold insert and/or other component of the mold;"). The cooling process is modeled with consideration for at least the heat capacity by which the thermal mass can be obtained ((Patel, Page 4, Lines 30-34) "As for the filling process, the equations for modelling the cooling process depend on material properties of the material from which the part is to be molded, such as viscosity, heat conductivity, heat capacity, coefficients of thermal expansion, elasticity, etc. and on process conditions, such as temperature, pressure, etc"). The cycle time of the injection molding process is used as a design criteria, wherein the cycle time is highly dependent upon the cooling time of the of material, thereby indicating that the cycle time would be indicative of a baseline thermal behavior ((Patel, Page 8, Lines 10-13) "In some embodiments, the iterative optimization process seeks to optimize one or more of the following alternative or additional parameters: - Lifetime of the mold component (number of shots); - cycle time of injection molding process."); ((Patel, Page 8, Lines 16-18) "For example, the cycle time may be a direct result of the simulation process, e.g. as the accumulated time for the simulated filling, cooling and ejection processes."); ((Patel, Page 9, Lines 3-6) "The process may comprise repeating the computer-implemented optimization process so as to provide multiple alternative three-dimensional representations of a mold component, e.g. multiple alternatives fulfilling a number of design criteria (e.g. within boundary conditions defining target tolerances, cycle times, etc.).")
determining the conformal cooling arrangement based on the identified hotspots, Hotspots are described as being identified in at least steps S34 and S35. ((Patel, Page 18, Lines 3-4) "In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert.") When following the flowchart given in Fig. 3, the mold insert design modifications (See S39) is dependent upon such steps, thereby indicating that the cooling arrangement is determined based on the identified hotspots. The cooling arrangement may be conformal in nature, as discussed previously ((Patel, Page 5, Lines 16-20) "The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels."). wherein the cooling channel geometries and routing paths are automatically derived from the hotspot locations; The methodology in the flowchart depicted in Figure 3 is described as being performed by the mold insert optimizing module, wherein the mold insert optimization module is further described as being implemented by a programmed computer or software application, thereby indicating that this step is performed automatically ((Patel, page 13, Lines 23-30) "The data processing system 100 may be implemented by a suitably programmed computer or other computing infrastructure implementing a mold insert optimization module 110, a CAD modelling module 104, a database 105 for storing molding process parameters, a database 106 for storing mold insert manufacturing process parameters, a user interface module 103 and a model output module 102. The various modules may be implemented as respective software applications executed by the data processing system. It will be appreciated that some or all of the modules may be combined into a single software application."). Changes to the mold component include cooling channel geometry changes ((Patel, Page 7, Lines 13-17) "The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."). Design features of the insert also include the position (route path) and geometry of the cooling channels ((Patel, page 4, Lines 34-37) "It will further be appreciated that the cooling process depends on a number of features of the mold insert and/or other mold component, such as the cavity geometry, the material of the mold insert and/or other mold component, the number, positions and geometry of cooling channels, etc.")
automatically iteratively refining the conformal cooling arrangement by executing an additional predictive thermal model that accounts for the cooling channel design to identify any remaining hotspots and further optimize the cooling channel geometries; The process is depicted as occurring in an iterative loop to modify the mold insert design, wherein the loop considers an insert manufacturing simulation (S34), a virtual inspection step (S35), an injection molding simulation (S36), (as additional predictive models which may include thermal/cooling analysis and simulation), wherein the steps account for the modified mold insert design. (See Figure 3). The process steps identify hotspots and optimize mold insert designs comprising cooling channel geometries, as stated in the rejection of the limitations above. The process is performed as a computer-implemented process, thereby indicating automatic execution ((Patel, Page 11, Lines 13-35) "performing a computer-implemented optimization process for modifying the current three-dimensional digital model of the mold component, the optimization process comprising: a) performing a computer-implemented simulation of an injection molding process for injection molding the part using a mold component manufactured based on the current three-dimensional model of the mold component, the computer-implemented simulation process receiving the received values of the one or more molding process parameters and the received three-dimensional digital model of the part; the computer-implemented simulation process resulting in a three-dimensional model of an injection molded part; b) comparing the three-dimensional model of an injection molded part with the received three-dimensional digital model of the part to be injection molded to determine one or more tolerances of the injection model part; c) comparing the determined tolerances with one or more target tolerances; and, if the determined tolerances are larger than the one or more target tolerances; automatically creating a modified three-dimensional digital model of the mold component and selecting the modified three-dimensional digital model of the mold component as the current three-dimensional digital model of the mold component; d) repeating steps a) through c) until the determined tolerances are no larger than the one or more target tolerances.")
[[determining sensor locations within the mold insert for embedding at least one sensor configured to measure one or more of temperature, pressure, and mold cycle events at the sensor locations;]]
forming the mold insert including the conformal cooling arrangement [[and the at least one embedded sensor within the mold insert,]] wherein the conformal cooling arrangement comprises cooling channels routed in proximity to the identified hotspots; and The mold component, which may be an insert, may be manufactured according to an additive process, wherein an additive process is understood to add material in incremental layers ((Patel, Page 9 Lines 20-23) "The manufacturing of the mold component may be performed in a variety of ways, dependent on the resulting choice of material from which the mold component is manufactured and the resulting geometry. Suitable manufacturing methods may include additive manufacturing such as 3D printing, molding, machining etc."); ((Patel, Page 18, Lines 31-34) "For example, while the above embodiments have mainly been described with reference to a mold insert, it will be appreciated that other embodiments may be used to design and manufacture other mold components."). The mold component design model used in the manufacturing (See Fig 3, S38 receiving the optimized mold insert design for manufacture) includes the arrangement of cooling channels ((Patel, Page 5, Lines 16-20, ¶) "The process may further receive information pertaining to the mold component: In particular, the process may receive an initial three-dimensional digital model - e.g. a CAD model - defining the geometry of the mold component. This design model may define a mold cavity conformal to the desired geometry of the molded part, an initial arrangement of gates and cooling channels."); ((Patel, Pages 7, Lines 13-17) "The step of automatically creating a modified three-dimensional digital model of the mold component may include changing the 3D geometry of the mold component. For example, when the mold component is a mold insert, changing the 3D geometry may e.g. include modifications of the cooling channels, gates, material properties, variations of the cavity volume so as to allow for shrinkage, and/or the like."). Hotspots are observed in the insert, in steps S34 and S35 as given above ((Patel, Page 18, Lines 3-4) "In particular, this step may utilize data from steps S34 and/or S35, such as determined residual stress/hotspots in the insert."). Because the hotspots are identified in the insert and the cooling channels are part of the insert, the cooling channels are clearly routed in some proximity to any identified hotspot, at least by association of both occurring in the same component.
forming the injection mold part by heating a source of material at the mold insert
and cooling the source of material by the conformal cooling arrangement.((Patel, Page 1, Lines 7-18) "Injection molding is a widely used manufacturing process for producing parts by injecting material into a mold. Injection molding can be performed with a host of materials including elastomers, thermoplastic and thermosetting polymers. Typical injection molding processes involve heating and melting the material, injecting the melted material into a mold cavity, allowing the injected material to cool and harden to the configuration of the cavity and ejecting the hardened part. Traditionally, once the part to be molded has been designed, usually by an industrial designer or an engineer, a tool maker has designed and precision machined a suitable mold from metal, such as steel or aluminium, so as to form the features of the designed part. The initial design and manufacture of the mold using traditional mold insert
manufacturing techniques is quite costly. Once a mold is manufactured it can be used, in some instances, to manufacture millions of parts"); ((Patel, page 8, Lines 18-19) "Accordingly, the process may provide a more efficient manufacturing process (e.g. by optimizing for the cycle time of the injection molding process)."); ((Patel, Page 1, Lines 21-24) "Examples of design features of an injection mold that influence the quality of the resulting part include that arrangement of gates though which the molten material is injected into the cavity, the arrangement of cooling channels through which coolant is passed so as to cool the injected material, the location of the parting lines, etc.")
Patel alone does not explicitly disclose or appear to contemplate the determination of sensor locations for embedding sensors within a mold insert.. However; Park discloses
determining sensor locations within the mold insert for embedding at least one sensor configured to measure one or more of temperature, pressure, and mold cycle events at the sensor locations; Sensors are placed at identified positions in the injection mold insert, wherein the sensors have corresponding holes by which to be integrated into the assembly as depicted in Figure 6.
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Sensors are described as being a temperature sensor and a pressure sensor ((Park, Page 54, ¶1) "There is also a constraint that the new cooling system is not allowed to interfere with ejection system, temperature sensor and pressure sensor")
and the at least one embedded sensor within the mold insert, The sensors are shown in Figure 6 as being placed in the cooling channels. The cooling channels are described as being manufactured via metal 3D printing technology ((Park, Page 49, ¶3) " Because of the advancement in metal 3D printing technology, the application of conformal cooling channels made by solid freeform fabrication is becoming popular recently. The conformal cooling channels system is recognized as one of the best solutions in reducing cycle time, differential shrinkage, and warpage defects on molded parts [6]. Although conformal cooling channels applied to injection mold is no longer new, the design and optimization of conformal cooling channels for special practical application is still a research problem. Ahn D.G et al. [7] studied on the manufacture of an injection mold for plastic fan with a pair of conformal cooling channels in each blade via laser-aided direct metal tooling process to achieve both rapid and uniform cooling characteristics"); ((Park, Page 57, ¶2) "After design and simulation, we decided to make the inserts. The two inserts were fabricated by selective laser melting method on MetalSys 150 3D printer with P21 material. The printing process and the result of one insert are shown in Figure 11a.")
Patel is analogous to the claimed invention because it is related to the same field of endeavor of optimizing cooling channel design in inserts for injection molding applications. Park is likewise analogous to the claimed invention because it pertains to the same field of endeavor of optimizing cooling channel design for injection molding applications. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have modified the disclosure of Patel to incorporate the teachings of Park because some teaching, suggestion, or motivation would have led one having ordinary skill to do so in order to arrive at the claimed invention. Park suggests that incorporating sensors into an injection molding insert may be beneficial for monitoring important locations of the mold so as to employ intelligent molding control. Accordingly, one having skill in the art would be motivated to incorporate such features to further enhance the teachings of Patel.
Claims 2, 3, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over the proposed combination as applied to claims 1 and 13 above, and further in view of Kumar et al (Kumar, S., Park, H., and Lee, C., “Data-driven smart control of injection molding process”, November 2020, CIRP Journal of Manufacturing Science and Technology, Volume 31, pp 439-449), hereinafter referred to as Kumar.
Regarding claim 2, the proposed combination discloses The method of claim 1, further comprising: as stated above. The proposed combination further in view of Park discloses (except the limitations surrounded by brackets ([[..]])) embedding the at least one sensor in the mold insert at the one or more sensor locations [[for providing a feedback loop that modifies a result of the predictive model.]] Locations of sensors are determined for a mold insert, as depicted in Figure 6. A mold insert is manufactured according to the design, as shown in Figure 11. The actual placement and utilization of the sensors embedded in the insert is suggested in a subsequent phase of research ((Park, page 58, ¶4) " By using the sensor system on the second phase of our project, the temperature and pressure at considered (important) locations in the mold will be monitored; the intelligent molding control system will be developed and implemented based on the thermal and mechanical behaviour happen in the mold. The productivity and the quality of the molding process will be consistent and reach the optimum value.").
The proposed combination does not disclose using the sensors for providing feedback to affect the result of the predictive model; however, Kumar discloses for providing a feedback loop that modifies a result of the predictive model Sensor data is collected for process condition monitoring to provide feedback for adjusted process parameters control ((Kumar page 449, Col 1, ¶2) "This paper presented an engineering analysis model to analyze the process behavior if the injection molding in a cyber way because a fully experimental approach is a lengthy, costly, and impractical option. Conventionally this understanding is completely dependent on the operator’s feedback. The cyber model experiment is supported by real experiments for data collection and process understanding. The analysis of the collected data from the cyber model and real factory experiments resulted in the design of the process control boundary for the product (car door trim). "). The real collected data from sensors is used to validate a cyber model of the system ((Kumar, Page 442, Col 1, ¶3) " Virtual temperature and pressure sensors are assumed in the cyber molding experiments. In addition to the virtual model analysis real data is also collected for its relative validation ")
Kumar is analogous to the claimed invention because it is related to the same field of endeavor of process optimizations in injection molding applications. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have modified the proposed combination of Patel and Park with the teachings of Kumar because some teaching, suggestion, or motivation would have led one having skill in the art to do so in order to arrive at the claimed invention. Patel discloses an optimization process for generating an optimal cooling insert design for an injection molding process, with consideration for injection molding process parameters in simulation steps of the optimization. Park discloses employing embedded sensors within the mold insert for injection molding process monitoring and intelligent molding control. Kumar discloses a control algorithm that leverages obtaining sensor information in order to adjust/predict optimal injection molding process parameters. Kumar further discloses using a cyber engineering analysis model for predicting/estimating process behavior for an injection molding process ((Kumar, Page 440, Col 2, ¶5) "So, for a detailed description of the process behavior of the manufacturing of car door trim with injection molding, a cyber engineering analysis model is developed as shown in Fig. 1. The geometric modeling of the cooling channels, gates, mold, as well as the product is precisely identical to the real counterparts. In different phases of the complete molding process, cooling is the most time- intensive. The developed cyber engineering model also helps in reducing the number of required real-world experiments and associated costs."). By incorporating cyber engineering analysis model validation via collected sensor data during a real process, as disclosed by Kumar, using the sensor-enabled insert during an injection molding process as disclosed by Park and using the injection molding process simulation disclosed by Patel, one would arrive at the claimed invention. One would have been motivated to make such a combination because Kumar explicitly suggests that injection molding process parameter optimization may be more integral for ensuring even cooling for mitigating defects than the mold design itself ((Kumar, Page 439, col 2, ¶1) " Although uneven cooling is a significant factor in quality defects, previous studies have indicated the choice of process and parameters influence the quality to a greater degree than the machine or mold design [5]"). Accordingly, It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have implemented have been obvious to validate the simulation model used in the disclosure of Patel using embedded sensor data as feedback so as to account for all influences which may affect the outcome of the even-ness of cooling when determining the optimal design for the actual mold or mold insert.
Regarding claim 3, the proposed combination discloses The method of claim 2, wherein the at least one sensor is configured for at least one of: as stated previously. The proposed combination in further view of Kumar discloses measuring temperature as a function of time, measuring pressure as a function of time, and identifying an opening and closing of a mold. Data obtained from sensors are described as being time-series data ((Kumar, Page 442, Col 1 ¶3-Col 2, ¶1) "The data obtained from cavity sensors are in the form of a time series and imported to a database in the company server as well as a local laptop as comma-separated files.")
It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have distinguished the type of data obtained by the sensors as disclosed by Kumar into the proposed combination because some teaching, suggestion, or motivation in the prior art references would have led one having skill in the art to combine the prior art references in order to arrive at the claimed invention. The proposed combination in particular view of Park discloses the utilization of both a pressure sensor and a temperature sensor but does not particularly disclose them in terms of generating measurements as a function of time. Kumar discloses the use of embedded sensors and specifically notes that the sensors produce time-series data. Kumar notes that the raw data from the sensors makes process monitoring more difficult and rather, features that can be extracted from the time series data can provide greater insights ((Kumar, Page 442, Col 2, ¶1- Page 443, Col 1, ¶1) "The time series data, if used directly, will make the process monitoring more difficult. Features like peak, average, maximum, and minimum are extracted from the raw data for the temperature and pressure profile respectively. These features reciprocate the process condition of the current and previous cycles."). Furthermore, the time-series simulation used in the design optimization process, as disclosed by Patel is highly focused consideration to the time-based elements of the simulation so as to optimize parameters such as cycle time in the injection molding process ((Patel, Page 15, Lines 22-25) " It will be appreciated that the simulation process may be an iterative process where various process parameters and/or the mold insert model may iteratively be modified so as to optimize for one or more parameters, such as manufacturing tolerances, cycle time, etc."). One having skill in the art would understand that having the corresponding time information reflective of the real injection molding process would be useful for validating the time-sensitive simulated model in the model validation process described in the rejection of claim 2. Accordingly, it would have been obvious to one having skill in the art to necessitate the utilization of time-series data from sensors so as to be able to gather greater insight over purely raw sensor data with no consideration to the time associated with it.
Regarding claim 14, the proposed combination discloses The method of claim 13, further comprising: as stated previously. The proposed combination in further view of Park and Kumar discloses embedding a sensor at the one or more sensor locations in the mold insert for providing a feedback loop that modifies a result of the predictive model. wherein such limitations are substantially similar to that recited in claim 2 but with respect for claim 13. Therefore, claim 14 is rejected under the same rationale as provided for claim 2.
Claims 6 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over the proposed combination, as applied to the claims 1, and 13 above, and further in view of Postawa et Al. (P. Postawa, D. Kwiatkowski, E. Bociaga, “Influence of the method of heating/cooling moulds on the properties of injection moulding parts”, June 2008, Archives of Materials Science and Engineering, Volume 31, Issue 2, Pages 121-124), hereinafter referred to as Postawa.
Regarding claim 6, the proposed combination discloses The method of claim 1, further comprising: stated above. The proposed combination does not disclose; however the proposed combination in view of Postawa discloses modifying the design so that the cooling flow geometry and direction from heat dissipation from the hotspots detected in the injection mold part is changed to reduce or eliminate the hotspots. Three different modified designs of cooling channels for the same mold part are shown with varied cooling flow geometry, where coolant flows according to the arrows on the diagrams (Postawa, Fig 1). Direction of heat dissipation correlates to a temperature gradient. ((Postawa, Page 122 Col 2 ¶2-3) "With this increase in coolant temperature less heat will be removed towards the end of the coolant flow (at the outlets) than is removed at the beginning of coolant flow (at the inlet), so it will produce a temperature gradient across the mould from the inlet to the outlet. These temperature gradients will affect the plastic parts cooling rate and part size, further slowing cycle time."). Detected hotspots in the part can be eliminated as a result of modifying the cooling channel design ((Postawa, Page 122 Col 2 ¶3 and Page 123 Col 1 ¶1) "Provided that the manifold and the supply and return pipework are correctly sized this arrangement will have twice the coolant flow volume through the mould, which is now capable of removing more heat from the mould metal and therefore the mould metal can cool the moulded part more quickly, removing more heat in the same cycle time (eliminating hot-spots) or removing the same heat in a shorter cooling time, leading to shorter cycle times.")
Postawa is related to the same field of endeavor as the claimed invention of injection molding, with particular interest of cooling methodologies for injection molded parts. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have incorporated design modifications for cooling channels in order to eliminate hotspots as taught by Postawa into the predictive modeling system taught by the proposed combination because some teaching in the art would have led one having skill to do so. Postawa discloses optimizing the cooling method yields the improvements of saving production time and increasing part quality. ((Postawa, Page 121 Col 1 ¶1) "The process cycle time in injection moulding process depends greatly on the cooling time of the plastic part, which is facilitated by the cooling channels in the injection mould. Effective cooling channel design in the mould is important because it not only affects cycle time but also the part quality"); ((Postawa, Page 121 Col 2 ¶1) "The cost efficiency of production is largely determined by whether the mould is a good or a poor conductor of heat. If the quality of the moulded part is to be enhanced and production time reduced, it is necessary to understand the laws that govern the exchange of heat in the mould and to apply these on a selective basis [7-24]"). Accordingly, to achieve such benefits, one would have been motivated to make such a modification in the cooling channel design optimization process disclosed by the proposed combination.
Regarding claim 17, the limitations The method of claim 13, further comprising: modifying the design so a cooling flow geometry of the cooling channel geometries and a direction from heat dissipation from hotspots detected in the injection mold part is changed to reduce or eliminate the hotspots. are substantially similar to that of claim 6 but with respect to independent claim 13 and so claim 17 is therefore rejected under the same rationale as provided for claim 6.
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over the proposed combination as applied to claim 6 above, and further in view of Zhou et al (Zhou, J., Turng, L., “Process Optimization of Injection Molding Using an Adaptive Surrogate Model with Gaussian Process Approach”, March 2007, Polymer Engineering & Science, Volume 47, Issue 5), hereinafter referred to as Zhou.
Regarding claim 7, the proposed combination discloses The method of claim 6, as stated previously.
The proposed combination in further view of Patel discloses (except the limitations surrounded by brackets ([[..]])) [[wherein the hotspots are digital representations]] of the injection mold part, and are [[emulated]] in response to analyzing, by the predictive model, the design. A cooling simulator that contains a heat transport model is discussed for simulating the cooling process of the material of the injection mold part after (in response to) ((Patel, page 16, Lines 16-21) " The cooling simulator 117 is configured to simulate the cooling process of the material inside the mold cavity. This process may e.g. be modelled by a discretized heat transport model based on discrete volume elements of the mold cavity and the mold insert. The model may model the heat transport inside the material that has been injected into the mold cavity, the heat transport into the mold insert and the heat transport to the surrounding, e.g. by the flow of coolant through the cooling channels of the mold insert."). The cooling simulator is done after (in response to) the analysis of the design in the predictive model discussed as part of the optimizer engine (Patel, Fig 3). An optimizer engine includes predictive iterative simulation models of the mold insert manufacturing process to optimize a design and the associated parameters of the mold insert, based on the provided CAD design at the CAD module. ((Patel, Page 15, Lines 11-17) " The optimizer engine 111 initially executes the simulator 112 to perform a simulation of the mold insert manufacturing process based on the received CAD model of the mold insert and the associated mold insert manufacturing process parameters. The simulation of the mold insert manufacturing process results in a model of the manufactured mold insert. It will be appreciated that the simulation process may be an iterative process where various process parameters and/or the mold insert model may iteratively be modified so as to optimize for one or more parameters, such as production cost, etc.
The proposed combination discloses in further view of Park (except the limitations surrounded by brackets ([[..]])) wherein the hotspots are digital representations hot regions are identified as heat map values in a digital representation of a molded part in Figure 2. … [[emulated]].
It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have incorporated the description of the hotspot regions as digital representations, as disclosed by Park, into the proposed combination because combining known elements according to known methods would yield predictable results. The proposed combination in view of Patel discloses a cooling simulator but does not disclose particular implementation details of the cooling simulator. Parks provides an exemplary representation of results of thermal simulation, wherein the heatmap indicators for thermal analysis are well-understood and predictable results of simulated heat transfer models. Accordingly, combining the prior art references according to known methods would yield the claimed invention and therefore the combination would have been obvious to a person having skill in the art.
The proposed combination does not disclose; however, the proposed combination in view of Zhou discloses emulated A surrogate model is used to predict an optimal solution ((Zhou, page 687, Col 1, ¶1) " It enables a continuous adaptive processing which the procedure will optimize the current version of the surrogate model, adaptively update this surrogate model whenever new data becomes available, and search for the optimal solution with guidance"); ((Zhou, Page 689, Col 1 ¶2) " The new optimization procedure with the GP modeling approach will intelligently identify the points with a large variance in the design space and select those as the next sampling points to adaptively update and improve the surrogate model. The optimization procedure includes the following two stages: the training stage (cf. Fig. 3) and the iteration stage (cf. Fig. 4). Either the convergence of the surrogate model or the convergence of the optimal solution can be used as the termination criteria")
Zhou is analogous art because it is reasonably pertinent to the problem faced by the inventor, which is to determine optimal designs for components within injection molding processes. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have incorporated a surrogate model in place of the pure simulation model, as disclosed by the other prior art references in the proposed combination because some teaching, suggestion, or motivation would have led one having ordinary skill in the art to combine the prior art references in order to arrive at the claimed invention. Patel and Park of the proposed combination all disclose the use of simulation for thermal analysis purposes for design optimization of injection mold inserts. Zhou discloses the utilization of a surrogate model to replace traditional simulations in design optimization tasks for injection molding, though not particularly with regard to injection mold insert design. However, Zhou also notes that the optimization scheme is generic and nature and can be applied to optimization objectives that are directly correlated with objectives that can be optimized using injection molding cooling inserts ((Zhou, Page 688, Col 1 ¶1) " This allows a variety of optimization objectives, such as a shorter cycle time, temperature uniformity, reduced residual stresses, minimal part shrinkage and warp-age, or some combination thereof, depending on the user’s requirements."). By applying the surrogate model (as an emulation) to the process disclosed by the proposed combination in place of the simulations, one having skill would arrive at the claimed invention. Zhou notes that the utilization of surrogate models in injection molding design optimization process offers an advantage over traditional simulations because the surrogate model allows for design optimizations to be evaluated in a reasonable timeframe ((Zhou, Page 684, col 2, ¶3) " To facilitate the optimization process for injection molding while avoiding an excessive number of numerical iterations using computationally intensive simulations, an alternative and more effective approach is adopted in this study. The idea is to use Gaussian process(GP), a nonlinear statistical regression technique, and design of computer experiments to establish a surrogate e model that can substitute tedious simulations while using minimum computational resources and intelligently selecting new sampling points in the design space, so that a large amount of process (or design) alternatives can be evaluated in a reasonable timeframe during a system-level optimization process"). Accordingly, it would have been obvious to combine the prior art references in order to arrive at the claimed invention so as to realize the advantages.
Claims 8 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over the proposed combination as applied to claims 1 and 13 above, and further in view of Brooks et al. (Hadley Brooks, Kevin Brigden, “Design of conformal cooling layers with self-supporting lattices for additively manufactured tooling”, 2016, Additive Manufacturing, Volume 11, pp. 16-22), hereinafter referred to as Brooks.
Regarding claim 8, the proposed combination discloses The method of claim 1, as stated previously.
The proposed combination does not disclose; however the proposed combination in view of Brooks discloses further comprising forming at least one lattice matrix into cooling channels of the conformal cooling arrangement. A lattice structure is integrated into conformal cooling layers for an injection molding application. (Brooks, Figs 1, 2, 7, 10, and 11); ((Brooks, Page 17 Col 1 ¶4) "The primary aim of this paper is to design and test conformal cooling layers with easy to build support lattices for efficient and balanced heat transfer. First the general design methodology for creating conformal layers is described. Then the experimental method is presented including the design and testing of simplified test pieces. Finally a virtual injection moulding case study is used to demonstrate the benefits of the method when applied to injection moulding"); ((Brooks, Page 17 Col 1 ¶6) "A lattice structure is then created by patterning unit cells to fill the overall conformal layer dimensions. The two models are then superimposed and any redundant lattice structure may be removed."); ((Brooks, Page 20 Col 1 ¶4) "A virtual case study was carried out in order to compare the performance of conformal cooling layers with conventional and conformal cooling channels. The focus of the case study is an injection moulded rectangular enclosure").
Brooks is analogous art because it is related to the same field of endeavor of additive manufacturing, and particularly involves discussion of injection molding cooling structures. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have substituted the conformal lattice structure for cooling as taught by Brooks into the conformal cooling channels taught by Patel for the predictable improvement of better thermal management, which increases production and improves part quality. ((Brooks, Page 21 Col 2 ¶3 and Page 22 Col 1 ¶1-2) "Conventionally drilled channels in tooling are not capable of achieving optimal geometries for complex impression shapes in a balanced fashion. In order to overcome these short falls additive manufacturing is currently being adopted to manufacture conformal cooling channels. Whilst significantly increasing performance, the design of these cooling channels is often time intensive and are still restricted by design rules required to minimise uneven cooling. To overcome these limitations new conformal cooling layers with self-supporting lattice structures are introduced. The lattices are constructed from simple unit cells and designed with self-supporting angles for AM. The effectiveness of the cooling layers was verified via experimental testing and simulation. The lattice structures were found to increase heat transfer over circular channels due to increased interfacial surface areas and fluid vorticity. Simulations, which were verified by experimental data, showed significantly lower thermal gradients on the heated surface. The cooling layers are likely to find applications in high performance tooling were high heat transfer rates and/or thermal balancing is critical. Examples could include injection moulding, blow moulding, extrusion and die casting")
Regarding claim 18, the proposed combination in view of Brooks discloses the limitations The method of claim 13, further comprising forming at least one lattice matrix into cooling channels of the conformal cooling arrangement. The limitations are substantially similar to that of claim 8 but with respect to claim 13 and so claim 18 is therefore rejected under the same rationale as provided for claims 8 and 13.
Claim 9 is rejected under 35 U.S.C. 103 as being unpatentable over the proposed combination as applied to claim 1 above, and further in view of Ogorodnyk et al. (Olga Ogorodnyk and Kristian Martinsen, “Monitoring and control for thermoplastics injection molding A review”, 2018, Procedia CIRP, Volume 67, pp 380-385), hereinafter referred to as Ogorodnyk.
Regarding claim 9, the proposed combination discloses The method of claim 1, further comprising: as stated previously.
The proposed combination does not disclose; however, the proposed combination in view of Ogorodnyk discloses executing an artificial intelligence process to calculate data metrics in response to forming the injection mold part from the formed mold insert; and When read in light of the specification, data metrics may include cycles, temperature, and pressure (Instant specification, ¶70). Ogorodnyk teaches process parameters to include temperature and pressure collected during the injection molding process ((Ogorodnyk, Page 381 Col 1, ¶1) "The middle one (process control) includes such variables as in-mold temperature and pressure."). The use of artificial intelligence to calculate process parameters is described. ((Ogorodnyk, Page 381 Col 2 ¶2) "In order to build the model different artificial intelligence methods can be used to process big amounts of data received during the process run.").
inputting the data metrics to the predictive model. Process parameters are analyzed by an AI method and applied to a model ((Ogorodnyk, Page 381, col 1 ¶5 and col 2 ¶1) "Among others, in the metamodel-based methods group ANN is mentioned. This is one of the artificial intelligence methods that can be applied to build mathematical models of injection molding process with consideration of the most important parameters. When the data is analyzed and model is build, the model can be used in order to adjust the current parameters’ values to receive a high-quality product as model and process output, as well as to shorten the cycle time"). Additionally, Ogorodnyk teaches that the outputs of an artificial neural network can be the basis for a predictive controller for injection molding. ((Ogorodnyk, Page 383 col 2 ¶5) "Hopmann, Ressmann [7] went further and propose to use a model predictive controller combined with artificial neural network to improve repeatability and product quality in plastic injection molding. “Unlike controllers such as proportional-integral- derivative controllers, the control output is not determined using a well-tuned, but mathematically relatively simple algorithm. Instead, it performs an online optimization based on a process model in order to obtain the control outputs” [7].") Furthermore, Ogorodnyk suggests AI for optimization of parameters can be applied to cooling systems for injection molding. ((Ogorodnyk, Page 381 Col 2 ¶2) "Among possibilities for process monitoring and control development is application of so-called methods of machine learning or artificial intelligence, for example, neural networks. This would allow to adjust values of necessary variables without involvement of machine operators if conditions change during the manufacturing process. These methods can also be used in rapid heating and cooling systems in micro injection molding [8, 9], as well as in injection molding of bigger components, such as LCD TV frame [10] and automotive interior part [11], for example.")
Ogorodnyk is analogous because it is related to the same field of endeavor of injection molding optimization techniques. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have implemented an artificial intelligence method to calculate and optimize data metrics such as pressure and temperature, as discussed by Ogorodnyk, for use as input of the predictive model taught by Patel because Ogorodnyk suggests the usage of AI parameter prediction for cooling systems in injection molding for optimal functionality and better quality of manufactured parts ((Ogorodnyk, Page 380 Col 2 ¶1-2) "One of the ways to shorten the cycle time and, in particular, the cooling stage, without compromising quality of manufactured parts is use of rapid heating and cooling systems, which can include application of variotherm technology and conformal cooling/heating channels. Process monitoring and control, as well as use of variotherm technology or conformal cooling/warming channels would benefit from application of artificial intelligence methods in order to function in the most optimal way."); ((Ogorodnyk, Page 381 Col 2 ¶2),"; ((Ogorodnyk, Page 381 Col 2 ¶2) "Among possibilities for process monitoring and control development is application of so-called methods of machine learning or artificial intelligence, for example, neural networks. This would allow to adjust values of necessary variables without involvement of machine operators if conditions change during the manufacturing process. These methods can also be used in rapid heating and cooling systems in micro injection molding [8, 9], as well as in injection molding of bigger components, such as LCD TV frame [10] and automotive interior part [11], for example."). Integrating artificial intelligence methods to predict process parameters offers the improvements of reducing complexity and having more accurate control, as compared to other methods, for achieving efficient cooling on injection molded parts ((Ogorodnyk, Page 384 Col 1 ¶3-5) "Quality issues are a common problem for injection molding process due to non-uniform temperature variation in the mold. During design of the molds for injection molding process, it is very difficult to achieve efficient cooling with uniform thermal distribution. It is attempted to be achieved through application of variotherm technology, as well as conformal cooling/heating channels. However, most of rapid heating and cooling systems are still difficult to apply in the mass production of plastic parts in injection molding industry due to extra complex heating setups, weak mechanical strength of the mold and lack of a standardized control option… Here different methods can be used, however, artificial intelligence methods will bring more benefits than the usual ones, as they can adjust and change the model and output parameters depending on changes of conditions and environment, as well as put aside parameters of the process that are not influencing the model to the high extent.")
Claims 10 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over the proposed combination as applied to claims 1 and 13 above, and further in view of Adriany et al. (US Patent Publication No. 2019/0086154 A1), hereinafter referred to as Adriany.
Regarding claim 10, the proposed combination discloses The method of claim 1, further comprising: as stated previously.
The proposed combination does not disclose; however, the proposed combination in view of Adriany discloses performing a part selection process including determining a part volume to surface area ratio; and Various testing apparatuses (parts) are presented for selection, with variation in their configuration ((Adriany, ¶25) "In some aspects, the angles of the at least one series of tapered edge ramps are selected from: 1, 15, 30, 45, 60, and 75 degrees."). See also Adriany ¶25-30 for additional variants of part parameters to be selected. A simulation of conformal cooling passages around multiple defined part shapes is done for comparison, whereby the surface-volume area is described for conformal cooling passages for a given part. One having ordinary skill in the art could similarly perform simulations of cooling configurations around various parts in order to inform part geometry selection based on the desired output. ((Adriany, ¶194) "A heat map simulation of a heat exchanger where the heat exchanger is a mold comprising conformal cooling passages about a central cavity defining a spherical shape (FIG. 15 and FIG. 21), or a polyhedron shape (FIG. 17 and FIG. 19) was calculated and compared to that of a mold comprising non-conformal cooling passages about a central cavity having a polyhedron shape FIG. 18) or non-conformal cooling passages abou1 a central cavity having a spherical shape (FIG. 22). The heat maps demonstrate that the simulated temperature difference across the central cavity is more homogeneous for the mold comprising conformal cooling passages. Furthermore, the temperature drop is greater for the fractal branched conformal cooling passages because the mold comprising the non-conformal cooling passage is a single passage where the heal transfer to the fluid is less because the single passage mold comprises a fluid which is increasing in temperature as the fluid traverses through the single passage. The fractal branched conformal cooling passages, however enable more efficient heat transfer because of the higher surface-volume area of the multiple passages, each of which is transporting a separate portion of the fluid.")
modifying the design of the injection mold part in response to the part volume to surface area ratio exceeding a predetermined threshold. A design file is provided and is used to create a testing apparatus (injection mold part) and the dimensions of the additively manufactured part are compared against the initial design to determine if the manufactured part dimensions exceed a set threshold. ((Adriany, ¶32) "In some aspects, this disclosure relates to a method of fabricating a testing apparatus for additive manufacturing processes, and using said testing apparatus to detect the presence of defects of a selected additive-manufacturing process. An illustrative embodiment of the method includes creating an input design file for a testing apparatus where the design file comprises size requirements of the testing apparatus features, performing an additive manufacturing process to the testing apparatus designed from the input design file, scanning a first side surface of the additively manufactured testing apparatus, measuring the dimensions of one or a plurality of the features positioned on the first side surface of the additively manufactured testing apparatus, and comparing the dimensions of one or a plurality of the features positioned on the first side surface of the additively manufactured testing apparatus with the first input design file size features. A difference greater than a set threshold in the dimensions of the additively manufactured testing apparatus and of the first input design file indicates a defect in the additive manufacturing process."). See also Figs 36 and 37 for graphs depicting discrepancies in a CAD design versus the manufactured part measurements. A simulation of conformal cooling passages around multiple defined part shapes is done for comparison, whereby the surface-volume area is described for conformal cooling passages for a given part. One having ordinary skill in the art could similarly perform simulations of cooling configurations around various parts in order to inform part geometry modifications based on the optimal output (Adriany, ¶194).
Adriany is analogous art because it is related to the same field of endeavor of injection mold inserts and utilizing conformal cooling. It would have been obvious to one of ordinary skill to which said subject matter pertains at the time the invention was filed to have implemented the determination of part volume to surface area ratio as a component of a part selection and design modification processes because a high surface area to volume ratio is a desirable quality in the art for efficient thermal management and thermal management is critical for ensuring part quality and reducing cycle time, thereby saving money and time. ((Adriany, ¶194) "The fractal branched conformal cooling passages, however. enable more efficient heat transfer because of the higher surface-volume area of the multiple passages, each of which is transporting a separate portion of the fluid."); ((Adriany, ¶18) "Conformally cooled molds are capable of yielding reduced cycle times and greater cooling uniformity, which is necessary for thin wall molding.").
Regarding claim 19, the proposed combination discloses The method of claim 13, further comprising: as stated previously.
The proposed combination discloses in further view of Adriany performing a part selection process including determining a part volume to surface area ratio; and
modifying the design of the injection mold part in response to the part volume to surface area ratio exceeding a predetermined threshold wherein the limitation are substantially similar to that recited in claim 10 and therefore rejected under the same provided rationale.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Patel, S., and Sudheendra, S., "A Simulation Study of Conformal Cooling Channels in Plastic Injection Molding", 2017, IJEDR, Vol. 5, Issue 1 discloses a simulation study of different cooling channels for injection molded plastic parts and compares their performances in terms of cooling time sand temperature profiles to determine the best solution.
Torres-Alba, A., Mercado-Colmenero, J., Diaz-Perete, D., and Martin-Donate, C., "A New Conformal Cooling Design Procedure for Injection Molding Based on Temperature Clusters and Multidimensional Discrete Models", January 7, 2020, Polymers, Volume 12, Issue 1 discloses a method of automated design for conformal cooling systems for injection molding technology.
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/E.G.L./Examiner, Art Unit 2187
/EMERSON C PUENTE/Supervisory Patent Examiner, Art Unit 2187
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