DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claims 1-20 are still pending in this Application.
Response to Amendments/Remarks
Applicant’s argument/remarks, on page 8, with respect to rejections to claims 1-20 under 35 USC § 112(b) have been fully considered and are persuasive. Therefore, rejections to the claims under 35 USC § 112(b) have been withdrawn.
Applicant’s argument/remarks, on pages 8-10, with respect to rejections to claims 1-20 under 35 USC § 101 have been fully considered and are respectfully unpersuasive. Therefore, rejections to the claims under 35 USC § 101 have been maintained.
On page 9, the Applicant argues that:
“Under the broadest reasonable interpretation of claim 1 by someone having ordinary skills in the art in view of the specification, at least the claim element "sending the selected HM configuration to a 3D printer for printing" amounts to an integration of the claimed subject matter into a practical application in accordance with MPEP 2106.04(d). In view of claim 3 of the Example 47 of the July 2024 Subject Matter Eligibility Examples, the patent eligibility analysis of claims 1, 11, and 20 would be similar to the analysis therein. Similar to the computational solutions provided in claim 3 of the Example 47, the claimed subject matter provides specific solutions in hybrid manufacturing that improves manufacturing configuration automation for user-specified objectives. Therefore, similar to the Example 47, the pending claims as a whole have integrated the recited judicial exception (if any) into a practical application (e.g., in hybrid manufacturing) of the exception. Therefore, the additional elements currently recited in the amended claim 1 have demonstrated that the subject matter therein has integrated the abstract ideas into practical applications, in accordance with MPEP 2106.04. Similar limitations are now in the independent claims 11 and 20. These claimed limitations amount to integration of practical application under the Prong Two analysis of Step 2A and renders the claims eligible under 35 U.S.C. § 101”. These arguments are respectfully unpersuasive.
The limitation “sending the selected configuration/data” from one computer device to another client computer device for printing is simply an intended use of the results of the abstract idea and does not constitute an integration into a practical application and/or does not include elements sufficient to amount to significantly more than the judicial exception. The Applicant cites claim 3 of example 47 which was found eligible under 101. However, this claim is not analogous or similar to the claimed subject matter in this Application. As a matter of fact, Example 47 Claim 2 is more similar to the claimed subject matter and involves the receiving of data, training of a model, detecting anomalies and generate anomaly data, and outputting data. The step of outputting data is similar to the sending of configuration data as recited in the claims of this application. This requires a generic output of computer. This limitation is merely a post-solution step of transmitting data output—a nominal addition to the claim that does not meaningfully limit the claim. Therefore, this step is an insignificant extra-solution activity.
Applicant’s arguments on pages 10-13, with respect to rejections to claims 1-20 under 35 USC § 103 have been fully considered and are persuasive. Therefore, rejections to the claims under 35 USC § 103 have been withdrawn.
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 2-4 and 12-14 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 pre-AIA the applicant regards as the invention.
Claims 2 and 12, respectively, recites the limitation "the two or more figures of merit” in line 2. There is insufficient antecedent basis for this limitation in the claim. It is unclear if the term “two or more figures of merit refers back to the term “various figures of merit…” previously recited.
For purposes of Examination, claims 2 and 12 will be interpreted as:
“… wherein each node corresponds to a vertex of a Pareto front with respect to two or more figures of merit of the various figures of merit”.
Claims 3 and 13, respectively, recites the limitation "the two or more figures of merit” in line 1. There is insufficient antecedent basis for this limitation in the claim. It is unclear if the term “two or more figures of merit refers back to the term “various figures of merit…” previously recited.
For purposes of Examination, claim 3 and 13 will be interpreted as:
“… displaying values of two or more figures of merit for the selected HM configuration”.
Claims 4 and 14, respectively, recites the limitation "the two or more figures of merit” in line 1. There is insufficient antecedent basis for this limitation in the claim. It is unclear if the term “two or more figures of merit refers back to the term “various figures of merit…” previously recited.
Claim 4 and 14, respectively, further recites “wherein the two or more figures of merit comprise a cost to print the 3D object, a time to print the 3D object, a material removal cost, a material removal time, or any combination thereof’. This is unclear and confusing because claim 1 already recites “cost to remove material”, “cost to print”, “time to print”. It is unclear if the term “a material removal cost” is different than “cost to remove material” as recited in claim 1 and 11, respectively.
For purposes of Examination, claims 4 and 14 will be interpreted as:
“… wherein two or more of the figures of merit further comprise the cost to print the 3D object, the time to print the 3D object, the cost to remove material, a material removal time, or any combination thereof”.
The applicant is welcome to amend the claims to overcome the rejections and clarify the subject matter recited.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1, 11, and 20 respectively recite:
“computing…., a graph of HM configurations based on the user input parameters, wherein the graph comprises a plurality of nodes corresponding to different configurations for manufacturing the 3D object, wherein the plurality of nodes comprises values for various figures of merit including cost to print, material cost, cost to remove material, overall cost, time to print, time to complete, and likelihood of print job failure or part failure”.
Under the broadest reasonable interpretation, the terms of the claim are presumed to have their plain meaning consistent with the specification as it would be interpreted by one of ordinary skill in the art. See MPEP 2111.
These limitations as drafted are a process that under its broadest reasonable interpretation, covers mathematical relationships and/or mental process which is identified as an example of mathematical concepts grouping of abstract ideas and/or mental processes steps. The graph computation is an abstract idea in itself because it refers to the generation and correlation of data or a data structure represented in a hierarchically/connected manner, and which is represented by circles (node of data) interlinked. The disclosures suggests, that each node represents a calculation of values with respect to two or more figures of merit such as values for various figures of merit including cost to print, material cost, cost to remove material, overall cost, time to print, time to complete, and likelihood of print job failure or part failure (see 0026, 0040, 0051 and 0079). Thus, the graphs and its nodes and the configuration represents calculated values/figures of merit with respect to the user input constraints/objectives representing manufacturing parameters/factors including feature modifications or direction of tensile loadings (0018), and which are optimized with respect to these factors, and/or user inputs. Optimization in the broadest reasonable interpretation refers to optimization algorithms which compute values using a series of mathematical calculations. The claim does not provide any details about how the computation of the values of each node is performed other than they are computed. Thus, these limitations or steps involve or suggest mathematical concepts and, thus, the claims recite an abstract idea/judicial exception. Furthermore, this steps covers steps of collection or observing data, evaluation/computation, and judgment/opinion which are steps that fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. (See MPEP 2106.04(a)(2), subsection III). For instance, one person can easily calculate the cost of printing an object given the cost of material and amount used and estimated removal time based on past experience or empirical data or collected input data collected by using pen and paper. The reciting of a computer and/or memory does not preclude these steps from practically being performed in the human mind or by using pen and paper. Additionally, the mere nominal recitation of control unit and/or computer components does not take the claim limitation out of the mental processes grouping. Thus, the claim recites a mental process.
The judicial exceptions above are not integrated into a practical application because the claims recites additional elements such as “receiving an object model of the 3D object, the object model being a computer aided design (CAD) file or a point cloud model”; “obtaining user input parameters describing one or more user objectives”, “a processing device and memory”, and “displaying a selected HM configuration corresponding to a selected node of the plurality of nodes”, and which are recited in high level of generality. The element/step of receiving an object model of the 3D object, the object model being a computer aided design (CAD) file or a point cloud model and obtaining user input parameters describing one or more user objectives” to be used in the abstract idea are recited in a high level of generality and considered insignificant extra solution and pre-solution activities of mere data gathering (see MPEP 2106.05(g)). The processing device and memory to perform the computation of values for a graph and to generate/display of a graph with nodes, which is also recited at high level of generality represents mere instructions to “apply” the abstract idea or to generally link the use of the judicial exception to a technological environment of an intended computer cannot provide an inventive concept as stated by the courts (see MPEP 2106.05(h)). Furthermore, “displaying a selected HM configuration corresponding to a selected node of the plurality of nodes”, and “sending the selected HM configuration to a 3D printer for printing” which are recited at high level of generality simply represents displaying/presenting data and are considered significant extra-solution activities (see MPEP 2106.05(d) and 2106.05 (g)). The preamble recites that the generation of the configuring/configuration is for making a 3D object using additive and subtractive manufacturing, and a 3D printer for printing, which are recited at high level of generality, is considered insignificant extra-solution activities of simply linking the abstract idea to a particular technological environment or field of use such as Hybrid manufacturing processes (see MPEP 2106.05h). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “receiving an object model of the 3D object, the object model being a computer aided design (CAD) file or a point cloud model”; “obtaining user input parameters describing one or more user objectives”, “a processing device and memory”, and “displaying a selected HM configuration corresponding to a selected node of the plurality of nodes”, and sending data which are recited at high level of generality are considered insignificant extra-solution activities. For instance, the element/step of “receiving an object model of the 3D object, the object model being a computer aided design (CAD) file or a point cloud model and obtaining user input parameters describing one or more user objectives” to be used in the abstract idea are recited in a high level of generality and considered insignificant extra solution and pre-solution activities of mere data gathering (see MPEP 2105.05 (g) See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015)). Also, “displaying a selected HM configuration corresponding to a selected node of the plurality of nodes”, and “sending/outputting the selected HM configuration to a 3D printer for printing” recited at high level of generality simply represents displaying/presenting data and are considered significant extra-solution activities which are a well-understood, routine, and conventional activity (see MPEP 2106.05(d)) and see MPEP 2106.05(g) collecting and outputting data are extra solution activities See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). The processing device and memory to perform the computation of values for a graph and to generate/display of a graph with nodes, which is also recited at high level of generality represents mere instructions to “apply” the abstract idea or to generally link the use of the judicial exception to a technological environment of an intended computer cannot provide an inventive concept as stated by the courts (see MPEP 2106.05(h) and 2106.05(f)). Thus, A generic computer and its memory for executing steps of a program are well understood, routine and conventional (see MPEP 2106.05(f)). Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic computer and its component or machinery to qualify as an improvement to an existing technology (see MPEP 2106.05(f)). The preamble recites that the generation of the configuring/configuration is for making a 3D object using additive and subtractive manufacturing, and a 3D printer for printing, which are recited at high level of generality, is considered insignificant extra-solution activities of simply linking the abstract idea to a particular technological environment or field of use such as Hybrid manufacturing processes (see MPEP 2106.05h). Accordingly, these additional elements do not integrate the abstract idea into a practical application, do not amount to significantly more than the judicial exception, and do not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are not patent eligible.
Claims 2-10, 12-19, depend from claims 1 and 11, respectively, and thus recite the limitations and the abstract ideas of their parent claims.
Claims 2-5, and 12-15 recites the additional limitations of “2 wherein each node corresponds to a vertex of a Pareto front with respect to the two or more figures of merit”, “3, displaying values of the two or more figures of merit for the selected HM configuration”, “4 wherein the two or more figures of merit comprise a cost to print the 3D object, a time to print the 3D object, a material removal cost, a material removal time, or any combination thereof”, “5 wherein the selected node comprises two or more sub-nodes, the method further comprising: enabling the user to select a target node of the two or more sub nodes”, and displaying an additional HM configuration corresponding to the target node”, which are recited at high level of generality and as stated above the steps of displaying in claims 3, 5, 13, and 15 represents displaying/presenting data and are considered significant extra-solution activities which are a well-understood, routine, and conventional activity (see MPEP 2106.05(d)) and see MPEP 2106.05(g) collecting and outputting data are extra solution activities See Mayo, 566 U.S. at 79, 101 USPQ2d at 1968; OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1092-93 (Fed. Cir. 2015). Also, claims 2 and 12 describe that the nodes corresponds to a vertex of a pareto front which is a mathematical concepts of optimization and thus represent an abstract idea of itself. Furthermore, Claims 4, and 14 discloses type of data being calculated by the abstract idea with respect to variable related to field of use such as hybrid manufacturing processes and are recited at a high level of generality and is considered insignificant extra-solution activities of simply linking the abstract idea to a particular technological environment or field of use such as Hybrid manufacturing processes (see MPEP 2106.05h). Accordingly, these additional elements do not integrate the abstract idea into a practical application, do not amount to significantly more than the judicial exception, and do not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are not patent eligible.
Claims 6-9 and 16-19 further recites “6, wherein the user input parameters comprise user selected portions of the 3D object that the user has identified as allowed or disallowed for having a support structure attached”, “7 wherein the user input parameters comprise user selected portions of the 3D object that the user has identified to be machine modified in a post printing process”, “8, wherein the user input parameters comprise user selected portions of the 3D object that the user has identified as being allowed or disallowed to modify the shape”, and “9 wherein computing the graph comprises computing the graph based in part on system constraints, wherein the system constraints comprise an overhang support threshold, a minimum feature size, or both”, which are recited at high level of generality and when interpreted broadly represent the data gathering of data to be used in the abstract idea and are considered insignificant extra solution activities of mere data gathering (see MPEP 2106.05(g)(3) and 2106.05(d)(ii)). These steps are necessary data gathering as an input to an equation or mathematical concepts as previously stated. Accordingly, these additional elements do not integrate the abstract idea into a practical application, do not amount to significantly more than the judicial exception, and do not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are not patent eligible.
Claim 10 further recites “printing the 3D object using a final HM configuration selected by the user and corresponding with a leaf node of the graph”, which is recited at high level of generality and is considered insignificant extra-solution activities of simply linking the abstract idea to a particular technological environment or field of use such as a 3D printing system (see MPEP 2106.05h). Accordingly, these additional elements do not integrate the abstract idea into a practical application, do not amount to significantly more than the judicial exception, and do not impose any meaningful limits on practicing the abstract idea. Therefore, the claims are not patent eligible.
Claim Rejections - 35 USC § 103
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.
Claim(s) 1, 4-6, 8-11, 14-16 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Reinhart et al (US 20200264589) in view of LV et al (CN 112238603A as supported by the machine translation provided), Wada et al (JP 2005025445A as supported by the machine translation provided), Agarwal et al (US 20230211561) and Nelaturi et al (EP 3206100 A1).
As per claim 1, Reinhart teaches a method of configuring for making a three-dimensional (3D) object by additive and subtractive hybrid manufacturing (HM) (see [0004] “In some embodiments, the operations include both additive manufacturing operations and subtractive-manufacturing operations. In some embodiments, each operation includes a region, a modifier, and a tool. In some embodiments, the data processing system performs hierarchical abstraction to partition the search into a plurality of domains. In some embodiments, the data processing system applies update rules or transformations to modify a state of the virtual workpiece…”), comprising:
receiving an object model of the 3D object, the object model being a computer aided design (CAD) file or a point cloud model (see [0053] “The system receives a computer-aided-design (CAD) model of a part to be manufactured and tools definitions of tools available for a manufacturing process (602)…”);
obtaining user input parameters describing one or more user objectives, (see Fig. 6 steps 602 receive CAD models and tools definitions; [0053] “The system receives a computer-aided-design (CAD) model of a part to be manufactured and tools definitions of tools available for a manufacturing process (602). "Receiving," as used herein, can include receiving via an interaction with a user…”; also, see [0021] user specified criteria);
computing, by a processing device, a graph of HM configurations based on the user input parameters (see Fig. 6 steps 602 and 604 the graph in steps 604 is generated based on the user inputs of steps 602; also, see [0020] “possible plans based on user specified criteria…” and [0022] and see [0054] “The system instantiates a virtual workpiece (604). The virtual workpiece corresponds to a physical workpiece from which the part to be manufactured can be physically manufactured. The virtual workpiece can be stored as a graph-based representation including a plurality of nodes and edges as described herein…”; also, see [0054-0058] “… 0057The system searches for combinations of the operations to be performed on the virtual workpiece to make the virtual workpiece correspond to the CAD model (610). This process can include performing hierarchical abstraction to partition the search into a plurality of domains. This process can include applying a cost function to select or eliminate some combination or operations… This process can include applying operations to the virtual workpiece, such as by applying update rules and/or transformations as described herein, to modify the state of the virtual workpiece…0058-0059 “[0058) The system identifies possible manufacturing solutions according to the search (612). The possible manufacturing solutions are the combinations of operations that can be performed on the virtual workpiece to make the virtual workpiece correspond to the CAD model. The possible manufacturing solutions can include both additive-manufacturing operations and subtractive-manufacturing operations. This process can include validating the possible manufacturing solutions against stored solutions or stored virtual workpieces…”; also, see [0029] and [0033]), wherein the graph comprises a plurality of nodes corresponding to different configurations for manufacturing the 3D object (see [0029] and [0033] and see [0054-0058] “…The virtual workpiece can be stored as a graph-based representation including a plurality of nodes and edges as described herein…”), wherein the plurality of nodes comprises values for various figures of merit including cost to print (see [0058] and [0059] ““…The selection criterion can be, for example, which possible manufacturing solution is least expensive to produce/cost to print…”), (see [0021] “…systems and methods for automated computer-aided process planning (CAPP) for hybrid manufacturing that can identify non-trivial, qualitatively distinct, and cost-optimal combinations of additive manufacturing/subtractive manufacturing techniques to produce a physical product from a workpiece, where the workpiece can be modified using additive-manufacturing operations in some portions and performing subtractive manufacturing operations on some portions”; also, see [0029], [0049]), (see 0059 “The selection criterion can be, for example, …which possible manufacturing solution is determined to be fastest to produce..”; also, see [0020]-[0021] and [0029] “splitting the graph represented by the partitioned solutions tree 122 into cells for efficient evaluation, and a cost function can be evaluated to determine a short list of the most promising manufacturing plans as feasible solutions 126…”; also, see [0044] and see [0059] “The system can select a manufacturing plan from the possible manufacturing solutions (614). This can include receiving a selection criterion and basing the selection on the selection criterion. The selection criterion can be, for example, which possible manufacturing solution is least expensive to produce, which possible manufacturing solution is determined to use the least amount of material, which possible manufacturing solution is determined to waste the least amount of material, which possible manufacturing solution is determined to be fastest to produce, or otherwise”, thus, the figure of merit refer to cost to produce/print, less material used, fastest time to produce; also, see 0049 cost;);
sending the selected HM configuration to a 3D printer for printing (see Fig. 1 manufacturing 128 and see [0030] “ Finally, one or more of the feasible solutions 126 can be sent for physical manufacturing 128 using the physical machinery and tools defined above for the tool entries 108, operations entries 110, and/or machining ontology 112. Physical manufacturing 128 produces a physical manufactured part from workpiece 130 according to one or more of the feasible solutions 126, for example as may be selected by a user, determined to be least expensive to produce, determined to use or waste the least amount of material, determined to be fastest to produce, or otherwise).
While Reinhart teaches displaying data, Reinhart does not explicitly teach wherein the one or more user objectives comprises at least one of a modifiable surface of the 3D object or a direction of tensile loading of the 3D object (this is interpreted in the BRI in light of the disclosure (0026 and 0039) as a constraint for the optimization method for a 3D printing model including no adding support structures or adding support), wherein the plurality of nodes comprises values for various figures of merit including material cost, cost to remove material, time to print, likelihood of print job failure or part failure, and displaying a selected HM configuration corresponding to a selected node of the plurality of nodes.
Lv teaches a method and system for generating 3D printing objects comprising obtaining user input parameters as one or more objectives/constraints, wherein the one or more user objectives comprises at least one of a modifiable surface of the 3D object (see the abstract “setting a constraint surface; the constraint surface refers to the area that is not allowed to add the support on the 3D model…adding scaffold and supporting structure; under the assistance of the scaffold and the supporting structure, realizing one time printing multiple 3 D model.”; also, see page 10 claim 2 “wherein the constraint surface is selected by the user through the frame selection, the constraint surface is the surface patch which does not allow to add the support structure to the three-dimensional model when the model is printed, and the constraint surface comprises one or more than one”; also, see page 3 par. 2 “the arranged to-be-printed 3 D model; adding scaffold and supporting structure; under the assistance of the scaffold and the supporting structure, realizing one time printing multiple 3 D model”; also, see Fig. 4 the lower face is modifiable so support structures are generated therein).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s invention to include input parameters as objectives/constraints, obtaining user input parameters as one or more objectives/constraints, wherein the one or more user objectives comprises at least one of a modifiable surface of the 3D object as taught by Lv in order to avoid modifying the object design by constraining the placing support structures on some regions for some 3D models that do not allow support to be added (see page 2 pars. 3-4 “…For example: dental model, sculpture, embossment, artwork and so on part surface is not allowed to be supported. The invention claims the area which is not allowed to be supported by the application as the constraint surface…”) and calculating a configuration that satisfy such constraint (see page 3 par. 14 “the scaffold structure of the invention can satisfy the model support constraint condition, as much as possible using the printing space once printing a plurality of models, which not only meets the requirement of the user model surface quality, but also can be suitable for mass production, greatly saves the labor and time cost”).
Reinhart-Lv does not explicitly teach wherein the plurality of nodes comprises values for various figures of merit including material cost, cost to remove material, time to print, likelihood of print job failure or part failure, and displaying a selected HM configuration corresponding to a selected node of the plurality of nodes.
However, Wada teaches an optimization system and method (see [0024] “In the optimization problem calculation method as one aspect of the present invention, the computer system searches for a solution of a combination optimization problem of a plurality of parameters by repeatedly updating and evaluating the solution candidates, and in the middle of the search process Generate dependency relationships between parameters based on solution candidate”) comprising computing a graph of optimized configurations (see [0018] “The graph structure is a figure composed of a plurality of nodes and links connecting the nodes. For example, it is possible to visualize the relationship between a plurality of parameters used in the optimization problem calculation by performing modeling such as assigning each parameter to a node and expressing a dependency relationship between parameters as a link”; also, see [0024]) and displaying a selected configuration corresponding to a selected node of the plurality of nodes (see [0024-0025] “…display the generated dependency relationship on a display device, provide the user with a user interface for editing the dependency relationship using an input device, and It is preferable that the search process is restarted while taking into account the dependency relationship edited by…”; also, see [0054] “…two nodes are selected…”; and see [0070-71] and [0079] “A “label” button is provided on the right side of the screen. When a “label” button is pressed after selecting a node (parameter) or a set of nodes (parameter block), a label input dialog is displayed on the screen. In this dialog, the label name to be given to the parameter or block can be input.”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include a step of computing a graph of optimized configurations and displaying a selected configuration corresponding to a selected node of the plurality of nodes as taught by Wada in order to display a selected HM configuration for a selected node of the system of Reinhart for allowing a user to visualize and understand the graph and parameters used in the optimization and also to visualize the best solutions found and values associated with the solutions (see Fig. 12 the best solutions are displayed; also, see [0018] and [0052] “By modeling the dependency relationship in this way, the relationship between a plurality of parameters used in the optimization problem calculation can be visualized, and the user can easily understand the relationship between the parameters. In the example of FIG. 8, it is intuitive that there is a strong dependency between Param1 and Param3, that Param2 and Param5 are blocked, and that Param4 is subordinate to a block consisting of Param2 and Param5 and Param3…”).
While Reinhart teaches finding solutions with respect to various figure of merit, Reinhart-Lv-Wada does not explicitly teach wherein the plurality of nodes comprises values for various figures of merit including material cost, cost to remove material, time to print, likelihood of print job failure or part failure.
Agarwal teaches a system and method for generating a configuration for printing an object (see 0035 and see Fig. 1 Am configuration component 140) comprising a step generating a configuration (see 0035 and see [0039] “…The profile 160 may further comprise optimization metrics pertaining to the AMC 140, which may be configured to quantify costs and/or loss associated with the AMC 140, a utility of the AMC 140, and/or the like…”, profile or optimized configuration is generated) including values of figures of merits including material cost (see [0110] “the AMC profile 160 may further comprise AMC optimization metrics (AMC metrics 170). The AMC metrics 170 may comprise any information for quantifying the suitability or optimality of an AMC 140. In some implementations, the AMC metrics 170 may comprise cost metrics 172 configured to quantify cost and/or loss factors associated with the AMC 140, which may include, but are not limited to: quantity of material consumed during fabrication under the AMC 140, material type, material cost, material waste, fabrication time (e.g., time required to fabricate AMO 18 in accordance with the AMC 140), complexity (e.g., complexity of the additive manufacturing process specified by the AMC 140), failure rate (e.g., failure rate of additive manufacturing processes implemented per the AMC 140)”), time to print (see [0110] “…fabrication time (e.g., time required to fabricate AMO 18 in accordance with the AMC 140), likelihood of print job failure or part failure (see [0110] “…failure rate (e.g., failure rate of additive manufacturing processes implemented per the AMC 140),…”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include steps of comprising generating a configuration including values of figures of merits including material cost, time to print, likelihood of print job failure or part failure as taught by Agarwal and include it in the one or more nodes of the graph in order to determine and optimize metrics or figures of merits such as cost and time by adjusting parameters of the object model to be printed while still satisfying constraints (see [0213] and [0269]).
While Reinhart-Agarwal teaches finding solutions with respect to various figure of merit, Reinhart-Lv-Wada-Agarwal still does not explicitly teach wherein the plurality of nodes comprises values for various figures of merit including cost to remove material.
However, Nelaturi teaches a system and/or method (see [0009]) comprising generating a graph of a configuration/actions with a plurality of nodes, wherein the plurality of nodes of a graph comprises values for various figures of merit including cost to remove material (see Fig. 12 nodes; also, see [0011] “One embodiment provides a system and method for planning of CNC machining operations with the aid of a
digital computer… A search engine repetitively transitions, starting at the initial state, from one of the states to another of the states by choosing one of the actions as guided by a heuristic that is based on aggregate cost and the negative volume that remains after subtracting the maximal sub-volume for the action chosen. A process plan is formed and includes each of the actions chosen when the negative 35 volume that remains is minimal. The tool is programmed with the process plan downloaded by the computer and includes machining operations by the tool based on the process plan…”; also, see [0042] “…FIGURE 12 is a diagram showing, by way of example, a search tree. Searching begins at an initial state 60, which forms the root node of the tree. The upper limit at the search frontier 61 pares down the search space. At first, the search will branch out quickly, but subsequently becomes greedy and only considers the best successor, that is, the most cost effective, action to transition from each state until the goal condition 62 is met. In practice, this approach produces near optimal plans because the heuristic is good at estimating the actual cost of removing the remaining material from the raw part or staging model. In a further embodiment, a pure greedy search can be run before running the variant of weighted A* search to establish an upper bound on the cost of the best plan…”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include generating a graph of a configuration/actions with a plurality of nodes, wherein the plurality of nodes of a graph comprises values for various figures of merit including cost to remove material as taught by Nelaturi in order to generate an optimal configuration with the lowest cost to produce an object (see [0011], [0020] “…The search engine as guided in choice of action by a heuristic, such as a cost constraint for minimizing manufacturing time and cost…”; also, see[0042]).
As per claim 4, Reinhart-Lv-Wada-Agarwal-Nelaturi teaches the method of claim 1, Reinhart further teaches wherein the two or more figures of merit comprise a cost to print the 3D object, a time to print the 3D object, a material removal cost, a material removal time, or any combination thereof (see [0059] “…The selection criterion can be, for example, which possible manufacturing solution is least expensive to produce/cost to print, which possible manufacturing solution is determined to use the least amount of material, which possible manufacturing solution is determined to waste the least amount of material, which possible manufacturing solution is determined to be fastest to produce/time to print, or otherwise; also, see Claim 1 above wherein the figure of merits recited herein were suggested or taught by the combination of references).
As per claim 5, Reinhart-Lv-Wada-Agarwal-Nelaturi teaches the method of claim 1, Reinhart further teaches wherein the selected node comprises two or more sub-nodes ( [0004 “…the virtual workpiece is stored as a graph-based representation including a plurality of nodes and edge…”), the method further comprising: enabling the user to select a target node of the two or more sub nodes (see Fig. 2 any of the nodes is selectable; also, see [0033], [0035], [0047] and [0054]);
However, Wada further teaches wherein a selected node comprises two or more sub-nodes (see [0054] ), the method further comprising: enabling the user to select a target node of the two or more sub nodes (see [0054] “When two nodes are selected after the “connect” button is pressed, a link from the previously selected node to the later selected node is generated. Thereby, the dependency relation between parameters can be added.), displaying an additional HM configuration corresponding to the target node (see [0024-0025] “…display the generated dependency relationship on a display device, provide the user with a user interface for editing the dependency relationship using an input device, and It is preferable that the search process is restarted while taking into account the dependency relationship edited by…”; also, see [0070-71] and [0079] “A “label” button is provided on the right side of the screen. When a “label” button is pressed after selecting a node (parameter) or a set of nodes (parameter block), a label input dialog is displayed on the screen. In this dialog, the label name to be given to the parameter or block can be input.”) ).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include a step of computing a graph of optimized configurations, wherein a selected node comprises two or more sub-nodes, the method further comprising: enabling the user to select a target node of the two or more sub nodes, and displaying an additional HM configuration corresponding to the target node as taught by Wada in order to display a selected HM configuration for a selected node of the system of Reinhart for allowing a user to visualize and understand the graph and parameters used in the optimization and also to visualize the best solutions found and values associated with the solutions (see Fig. 12 the best solutions are displayed; also, see [0018] and [0052] “By modeling the dependency relationship in this way, the relationship between a plurality of parameters used in the optimization problem calculation can be visualized, and the user can easily understand the relationship between the parameters. In the example of FIG. 8, it is intuitive that there is a strong dependency between Param1 and Param3, that Param2 and Param5 are blocked, and that Param4 is subordinate to a block consisting of Param2 and Param5 and Param3…”).
As per claim 6, Reinhart-Lv-Wada-Agarwal-Nelaturi teaches the method of claim 1, while Reinhart-Wada teaches an optimization system for finding optimized HM configurations/solutions or plans with respect to some user constraints, Reinhart-Wada does not explicitly teach wherein the user input parameters comprise user selected portions of the 3D object that the user has identified as allowed or disallowed for having a support structure attached (this is interpreted in the BRI as a constraint for the optimization method for a 3D printing model).
Lv further teaches a method and system for generating 3D printing objects comprising obtaining user input parameters as constraints, wherein the user input parameters comprise user selected portions of the 3D object that the user has identified as allowed or disallowed for having a support structure attached (see the abstract “setting a constraint surface; the constraint surface refers to the area that is not allowed to add the support on the 3 D model..”; also, see page 10 claim 2 “wherein the constraint surface is selected by the user through the frame selection, the constraint surface is the surface patch which does not allow to add the support structure to the three-dimensional model when the model is printed, and the constraint surface comprises one or more than one”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include input parameters as constraints, wherein the user input parameters comprise user selected portions of the 3D object that the user has identified as allowed or disallowed for having a support structure attached as taught by Lv in order to avoid placing support structures on some regions for some 3D models that do not allow support to be added (see page 2 pars. 3-4 “…For example: dental model, sculpture, embossment, artwork and so on part surface is not allowed to be supported. The invention claims the area which is not allowed to be supported by the application as the constraint surface…”) and calculating a configuration that satisfy such constraint (see page 3 par. 14 “the scaffold structure of the invention can satisfy the model support constraint condition, as much as possible using the printing space once printing a plurality of models, which not only meets the requirement of the user model surface quality, but also can be suitable for mass production, greatly saves the labor and time cost”).
As per claim 8, Reinhart-Lv-Wada-Agarwal-Nelaturi teaches the method of claim 1, while Reinhart-Wada teaches an optimization system for finding optimized HM configurations/solutions or plans with respect to some user constraints, Reinhart-Wada does not explicitly teach wherein the user input parameters comprise user selected portions of the 3D object that the user has identified as being allowed or disallowed to modify the shape (this is interpreted in the BRI I light of the disclosure (0026 and 0039) as a constraint for the optimization method for a 3D printing model including no adding support structures).
Lv teaches a method and system for generating 3D printing objects comprising obtaining user input parameters as constraints, wherein the user input parameters comprise user selected portions of the 3D object that the user has identified as being allowed or disallowed to modify the shape (see the abstract “setting a constraint surface; the constraint surface refers to the area that is not allowed to add the support on the 3D model..”; also, see page 10 claim 2 “wherein the constraint surface is selected by the user through the frame selection, the constraint surface is the surface patch which does not allow to add the support structure to the three-dimensional model when the model is printed, and the constraint surface comprises one or more than one”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include input parameters as constraints, wherein the user input parameters comprise user selected portions of the 3D object that the user has identified as being allowed or disallowed to modify the shape as taught by Lv in order to avoid modifying the object design by constraining the placing support structures on some regions for some 3D models that do not allow support to be added (see page 2 pars. 3-4 “…For example: dental model, sculpture, embossment, artwork and so on part surface is not allowed to be supported. The invention claims the area which is not allowed to be supported by the application as the constraint surface…”) and calculating a configuration that satisfy such constraint (see page 3 par. 14 “the scaffold structure of the invention can satisfy the model support constraint condition, as much as possible using the printing space once printing a plurality of models, which not only meets the requirement of the user model surface quality, but also can be suitable for mass production, greatly saves the labor and time cost”).
As per claim 9, Reinhart-Lv-Wada-Agarwal-Nelaturi teaches the method of claim 1, Reinhart further teaches wherein computing the graph comprises computing the graph based in part on system constraints (see [0043] “…An update rule can combine modifications 402, constraints 404, and costs 406… Constraints 404 can include disallow rotation 310, check bit dimensions 336, and enforce depth and diameter 328. Costs 406 can include costs from RDM and diameter 338.”), wherein the system constraints comprise an overhang support threshold, a minimum feature size, or both (see [0043] “Constraints 404 can include disallow rotation 310, check bit dimensions 336, and enforce depth and diameter 328”, thus, minimum feature size). Wada further teaches an optimized solution is determined based on constraints including a minimum feature size (see [0037] “In addition, as a parameter constraint condition, a range of values that the parameter can take (maximum value and minimum value”).
As per claim 10, Reinhart-Lv-Wada-Agarwal-Nelaturi teaches the method of claim 1, Reinhart further teaches comprising printing the 3D object using a final HM configuration selected by the user and corresponding with a leaf node of the graph (see Fig. 1 manufacturing the workpiece with the feasible solution 126; the lead node corresponds to the final feasible solution; also, see Fig. 6 step 614 and 616 and see [0059-0060]).
As per claim 11, Reinhart teaches an apparatus for configuring for making a three dimensional (3D) object by additive and subtractive hybrid manufacturing (HM) (see [0003]-[0004]; also, see Fig. 1 and Fig. 7 system and apparatus), the apparatus comprising:
a memory (see Fig. 7 memory 708 ad 726);
a processing device operatively coupled to the memory, the processing device to (see Fig. 7 processor 702):
receive an object model of the 3D object, the object model being a computer aided design (CAD) file or a point cloud model (see [0053] “The system receives a computer-aided-design (CAD) model of a part to be manufactured and tools definitions of tools available for a manufacturing process (602)…”);
obtain user input parameters describing one or more user objectives (see Fig. 6 steps 602 receive CAD models and tools definitions; [0053] and see [0021]; also, see claim 1 above for explanation of the rationale), (see Fig. 6 steps 602 receive CAD models and tools definitions; [0053] “The system receives a computer-aided-design (CAD) model of a part to be manufactured and tools definitions of tools available for a manufacturing process (602). "Receiving," as used herein, can include receiving via an interaction with a user…”; also, see [0021] user specified criteria);
compute a graph of (hybrid manufacturing) HM configurations based in part on the user input parameters (see Fig. 6 steps 602 and 604 the graph in steps 604 is generated based on the user inputs of steps 602; also, see [0020], [0022], [0054], [0054-0058]; see 0058-0059 “[0058) The system identifies possible manufacturing solutions according to the search (612). The possible manufacturing solutions are the combinations of operations that can be performed on the virtual workpiece to make the virtual workpiece correspond to the CAD model. The possible manufacturing solutions can include both additive-manufacturing operations and subtractive-manufacturing operations. This process can include validating the possible manufacturing solutions against stored solutions or stored virtual workpieces…”; also, see [0029] and [0033]; also, see claim 1 above for explanation of the rationale), wherein the graph comprises a plurality of nodes corresponding to different configurations for manufacturing the 3D object (see [0029] and [0033] and see [0054-0058] “…The virtual workpiece can be stored as a graph-based representation including a plurality of nodes and edges as described herein…” ), wherein the plurality of nodes comprises values for various figures of merit including cost to print (see [0058] and [0059] “…The selection criterion can be, for example, which possible manufacturing solution is least expensive to produce/cost to print…”), (see [0021] “…systems and methods for automated computer-aided process planning (CAPP) for hybrid manufacturing that can identify non-trivial, qualitatively distinct, and cost-optimal combinations of additive manufacturing/subtractive manufacturing techniques to produce a physical product from a workpiece, where the workpiece can be modified using additive-manufacturing operations in some portions and performing subtractive manufacturing operations on some portions”; also, see [0029], [0049]), (see 0059 “The selection criterion can be, for example, …which possible manufacturing solution is determined to be fastest to produce..”; also, see [0020]-[0021] and [0029] “splitting the graph represented by the partitioned solutions tree 122 into cells for efficient evaluation, and a cost function can be evaluated to determine a short list of the most promising manufacturing plans as feasible solutions 126…”; also, see [0044] and see [0059] “The system can select a manufacturing plan from the possible manufacturing solutions (614). This can include receiving a selection criterion and basing the selection on the selection criterion. The selection criterion can be, for example, which possible manufacturing solution is least expensive to produce, which possible manufacturing solution is determined to use the least amount of material, which possible manufacturing solution is determined to waste the least amount of material, which possible manufacturing solution is determined to be fastest to produce, or otherwise”, thus, the figure of merit refer to cost to produce/print, less material used, fastest time to produce; also, see 0049 cost;);
also, see claim 1 above for explanation of the rationale);
sending the selected HM configuration to a 3D printer for printing (see Fig. 1 manufacturing 128 and see [0030] “ Finally, one or more of the feasible solutions 126 can be sent for physical manufacturing 128 using the physical machinery and tools defined above for the tool entries 108, operations entries 110, and/or machining ontology 112. Physical manufacturing 128 produces a physical manufactured part from workpiece 130 according to one or more of the feasible solutions 126, for example as may be selected by a user, determined to be least expensive to produce, determined to use or waste the least amount of material, determined to be fastest to produce, or otherwise).
While Reinhart teaches displaying data, Reinhart does not explicitly teach wherein the one or more user objectives comprises at least one of a modifiable surface of the 3D object or a direction of tensile loading of the 3D object (this is interpreted in the BRI in light of the disclosure (0026 and 0039) as a constraint for the optimization method for a 3D printing model including no adding support structures or adding support), wherein the plurality of nodes comprises values for various figures of merit including material cost, cost to remove material, time to print, likelihood of print job failure or part failure, and displaying a selected HM configuration corresponding to a selected node of the plurality of nodes.
Lv teaches a method and system for generating 3D printing objects comprising obtaining user input parameters as one or more objectives/constraints, wherein the one or more user objectives comprises at least one of a modifiable surface of the 3D object (see the abstract “setting a constraint surface; the constraint surface refers to the area that is not allowed to add the support on the 3D model…adding scaffold and supporting structure; under the assistance of the scaffold and the supporting structure, realizing one time printing multiple 3 D model.”; also, see page 10 claim 2 “wherein the constraint surface is selected by the user through the frame selection, the constraint surface is the surface patch which does not allow to add the support structure to the three-dimensional model when the model is printed, and the constraint surface comprises one or more than one”; also, see page 3 par. 2 “the arranged to-be-printed 3 D model; adding scaffold and supporting structure; under the assistance of the scaffold and the supporting structure, realizing one time printing multiple 3 D model”; also, see Fig. 4 the lower face is modifiable so support structures are generated therein).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s invention to include input parameters as objectives/constraints, obtaining user input parameters as one or more objectives/constraints, wherein the one or more user objectives comprises at least one of a modifiable surface of the 3D object as taught by Lv in order to avoid modifying the object design by constraining the placing support structures on some regions for some 3D models that do not allow support to be added (see page 2 pars. 3-4 “…For example: dental model, sculpture, embossment, artwork and so on part surface is not allowed to be supported. The invention claims the area which is not allowed to be supported by the application as the constraint surface…”) and calculating a configuration that satisfy such constraint (see page 3 par. 14 “the scaffold structure of the invention can satisfy the model support constraint condition, as much as possible using the printing space once printing a plurality of models, which not only meets the requirement of the user model surface quality, but also can be suitable for mass production, greatly saves the labor and time cost”).
Reinhart-Lv does not explicitly teach wherein the plurality of nodes comprises values for various figures of merit including material cost, cost to remove material, time to print, likelihood of print job failure or part failure, and displaying a selected HM configuration corresponding to a selected node of the plurality of nodes.
However, Wada teaches an optimization system and method (see [0024] “In the optimization problem calculation method as one aspect of the present invention, the computer system searches for a solution of a combination optimization problem of a plurality of parameters by repeatedly updating and evaluating the solution candidates, and in the middle of the search process Generate dependency relationships between parameters based on solution candidate”) comprising computing a graph of optimized configurations (see [0018] “The graph structure is a figure composed of a plurality of nodes and links connecting the nodes. For example, it is possible to visualize the relationship between a plurality of parameters used in the optimization problem calculation by performing modeling such as assigning each parameter to a node and expressing a dependency relationship between parameters as a link”; also, see [0024]) and displaying a selected configuration corresponding to a selected node of the plurality of nodes (see [0024-0025] “…display the generated dependency relationship on a display device, provide the user with a user interface for editing the dependency relationship using an input device, and It is preferable that the search process is restarted while taking into account the dependency relationship edited by…”; also, see [0054] “…two nodes are selected…”; and see [0070-71] and [0079] “A “label” button is provided on the right side of the screen. When a “label” button is pressed after selecting a node (parameter) or a set of nodes (parameter block), a label input dialog is displayed on the screen. In this dialog, the label name to be given to the parameter or block can be input.”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include a step of computing a graph of optimized configurations and displaying a selected configuration corresponding to a selected node of the plurality of nodes as taught by Wada in order to display a selected HM configuration for a selected node of the system of Reinhart for allowing a user to visualize and understand the graph and parameters used in the optimization and also to visualize the best solutions found and values associated with the solutions (see Fig. 12 the best solutions are displayed; also, see [0018] and [0052] “By modeling the dependency relationship in this way, the relationship between a plurality of parameters used in the optimization problem calculation can be visualized, and the user can easily understand the relationship between the parameters. In the example of FIG. 8, it is intuitive that there is a strong dependency between Param1 and Param3, that Param2 and Param5 are blocked, and that Param4 is subordinate to a block consisting of Param2 and Param5 and Param3…”).
While Reinhart teaches finding solutions with respect to various figure of merit, Reinhart-Lv-Wada does not explicitly teach wherein the plurality of nodes comprises values for various figures of merit including material cost, cost to remove material, time to print, likelihood of print job failure or part failure.
Agarwal teaches a system and method for generating a configuration for printing an object (see 0035 and see Fig. 1 Am configuration component 140) comprising a step generating a configuration (see 0035 and see [0039] “…The profile 160 may further comprise optimization metrics pertaining to the AMC 140, which may be configured to quantify costs and/or loss associated with the AMC 140, a utility of the AMC 140, and/or the like…”, profile or optimized configuration is generated) including values of figures of merits including material cost (see [0110] “the AMC profile 160 may further comprise AMC optimization metrics (AMC metrics 170). The AMC metrics 170 may comprise any information for quantifying the suitability or optimality of an AMC 140. In some implementations, the AMC metrics 170 may comprise cost metrics 172 configured to quantify cost and/or loss factors associated with the AMC 140, which may include, but are not limited to: quantity of material consumed during fabrication under the AMC 140, material type, material cost, material waste, fabrication time (e.g., time required to fabricate AMO 18 in accordance with the AMC 140), complexity (e.g., complexity of the additive manufacturing process specified by the AMC 140), failure rate (e.g., failure rate of additive manufacturing processes implemented per the AMC 140)”), time to print (see [0110] “…fabrication time (e.g., time required to fabricate AMO 18 in accordance with the AMC 140), likelihood of print job failure or part failure (see [0110] “…failure rate (e.g., failure rate of additive manufacturing processes implemented per the AMC 140),…”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include steps of comprising generating a configuration including values of figures of merits including material cost, time to print, likelihood of print job failure or part failure as taught by Agarwal and include it in the one or more nodes of the graph in order to determine and optimize metrics or figures of merits such as cost and time by adjusting parameters of the object model to be printed while still satisfying constraints (see [0213] and [0269]).
While Reinhart-Agarwal teaches finding solutions with respect to various figure of merit, Reinhart-Lv-Wada-Agarwal still does not explicitly teach wherein the plurality of nodes comprises values for various figures of merit including cost to remove material.
However, Nelaturi teaches a system and/or method (see [0009]) comprising generating a graph of a configuration/actions with a plurality of nodes, wherein the plurality of nodes of a graph comprises values for various figures of merit including cost to remove material (see Fig. 12 nodes; also, see [0011] “One embodiment provides a system and method for planning of CNC machining operations with the aid of a
digital computer… A search engine repetitively transitions, starting at the initial state, from one of the states to another of the states by choosing one of the actions as guided by a heuristic that is based on aggregate cost and the negative volume that remains after subtracting the maximal sub-volume for the action chosen. A process plan is formed and includes each of the actions chosen when the negative 35 volume that remains is minimal. The tool is programmed with the process plan downloaded by the computer and includes machining operations by the tool based on the process plan…”; also, see [0042] “…FIGURE 12 is a diagram showing, by way of example, a search tree. Searching begins at an initial state 60, which forms the root node of the tree. The upper limit at the search frontier 61 pares down the search space. At first, the search will branch out quickly, but subsequently becomes greedy and only considers the best successor, that is, the most cost effective, action to transition from each state until the goal condition 62 is met. In practice, this approach produces near optimal plans because the heuristic is good at estimating the actual cost of removing the remaining material from the raw part or staging model. In a further embodiment, a pure greedy search can be run before running the variant of weighted A* search to establish an upper bound on the cost of the best plan…”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include generating a graph of a configuration/actions with a plurality of nodes, wherein the plurality of nodes of a graph comprises values for various figures of merit including cost to remove material as taught by Nelaturi in order to generate an optimal configuration with the lowest cost to produce an object (see [0011], [0020] “…The search engine as guided in choice of action by a heuristic, such as a cost constraint for minimizing manufacturing time and cost…”; also, see[0042]).
As to claim 14, this claim is the apparatus claim corresponding to the method claim 4 and is rejected for the same reasons mutatis mutandis.
As to claim 15, this claim is the apparatus claim corresponding to the method claim 5 and is rejected for the same reasons mutatis mutandis.
As to claim 16, this claim is the apparatus claim corresponding to the method claim 6 and is rejected for the same reasons mutatis mutandis.
As to claim 18, this claim is the apparatus claim corresponding to the method claim 8 and is rejected for the same reasons mutatis mutandis.
As to claim 19, this claim is the apparatus claim corresponding to the method claim 9 and is rejected for the same reasons mutatis mutandis.
As to claim 20, this claim is the apparatus claim corresponding to the method/apparatus claim 1 and 11 and is rejected for the same reasons mutatis mutandis.
Claim(s) 2 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Reinhart et al (US 20200264589) in view of LV et al (CN 112238603A as supported by the machine translation provided), Wada et al (JP 2005025445A as supported by the machine translation provided), Agarwal et al (US 20230211561) and Nelaturi et al (EP 3206100 A1) as applied to claim 1, and further in view of Nezhad et al (Pareto-based optimization of part orientation in Stereolithography”).
As per claim 2, Reinhart-Lv-Wada-Agarwal-Nelaturi teaches the method of claim 1, While Reinhart and Wada respectively teach finding a graph of nodes optimized configuration of parameters, Reinhart-Wada does not explicitly teach wherein each node corresponds to a vertex of a Pareto front with respect to the two or more figures of merit (Pareto front is a very well-known multi-objective optimization method, and which has been interpreted in the broadest reasonable interpretation in light of the disclosure as a Pareto efficient solution is one in which no single preference criterion can be made better without making another preference criterion worse.).
However, Nehad teaches an optimization method comprising a pareto based optimization algorithm (see the Abstract “The method proposed here handles several OFs individually. The objective functions are the build time and support volume under a desired surface finish. The optimization was performed using the multi-objective genetic algorithm (MOGA). At each genetic algorithm step, the surface finish was achieved by applying the adaptive layer thickness method. Pareto-based optimization finds a series of best part orientations with minimum build time and volume support”), wherein each node corresponds to a vertex of a Pareto front with respect to two or more figures of merit (see The Abstract “Pareto-based optimization finds a series of best part orientations with minimum build time and volume support”, the figures of merit are minimum build time and volume support for a node a such as orientation or solution found ; also, see page 1593 Col 1 par. 3 “The second method is to determine Pareto optimal solutions. A Pareto optimal set is a series of solutions that are not dominated by one another. From one Pareto solution to another, there might be a loss of one objective at the same time that the other is enhanced…”; also, see page 1593 Col 2 Par. 1 “…Therefore, it is a good method to demonstrate how Pareto based ranking and fitness sharing can be integrated in a multi-objective GA to find true Pareto fronts”; also, see page 1595 Col 2 last par. “…The OPBPO proposes seven orientations as Pareto front solutions (directions)”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include an optimization method comprising a pareto based optimization algorithm, wherein each node corresponds to a vertex of a Pareto front with respect to the two or more figures of merit as taught by Nehad in order to apply the pareto algorithm of Nehad to each node of the graph of Reinhart-Wada with respect to two or more figure of merits and generate a graph of printing configuration of nodes with pareto forms optimization based on a Mult objective optimization algorithm (see page 1592 col 1 par. 3 to page 1592 Col 2 par. 1 “This paper presents an optimized Pareto-based part orientation (OPBPO) algorithm to find out a series of the best part orientations considering the build time, support volume and surface finish, both simultaneously and independent… Here, build time and support volume were optimized as the objective functions in Pareto-based optimization using the multi-objective genetic algorithm (MOGA) method in the MATLAB toolbox. To evaluate the algorithm, several sample parts were checked”).
As to claim 12, this claim is the apparatus claim corresponding to the method claim 2 and is rejected for the same reasons mutatis mutandis.
Claim(s) 3 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Reinhart et al (US 20200264589) LV et al (CN 112238603A as supported by the machine translation provided), Wada et al (JP 2005025445A as supported by the machine translation provided), Agarwal et al (US 20230211561) and Nelaturi et al (EP 3206100 A1) as applied to claim 1, and further in view of Coffman et al (US 11698623).
As per claim 3, Reinhart-Lv-Wada-Agarwal-Nelaturi teaches the method of claim 1, Reinhart teaches the two or more figures of merit for the selected HM configuration (see 0059 cost, least amount of material, least wasted material) and Wada teaches displaying parameters and values (see Fig. 12) but Reinhart-Wada does not explicitly teach comprising displaying values of the two or more figures of merit for the selected HM configuration.
Coffman teaches a system and method comprising displaying values of the two or more figures of merit for a selected HM configuration (see Col 13 lines 65-66 “hybrid machines”; also, see Col 22 lines 31-45 “…An example of manufacture predictions displayed on a GUI is discussed below with reference to FIG. 13”; also, see Col 11 line 58-Col 12 line 21 “…Cycle time refers to the time it takes to manufacture a physical object not including the set-up time… Machine Cycle Time: the processing time of the machine working on a part… Overall Cycle Time: the complete time it takes to produce a single unit (this term is generally used when speaking of a single machine or process); 5) Total Cycle Time: this includes all machines, processes, and classes of cycle time through which a product must pass to become a finished product and other suitable categories…”; also, see Claim 1 “a graphical interface tool for providing predictions of manufacturing processes… wherein the at least one predictive value corresponds to one or more of the following: predicted cost, set-up time, cycle time, a number of Computer Numerical Control (CNC) operations, requirement of a mill machine, requirement of a lathe machine, requirement of a sheet metal process, a type of blank used, or a type of fixture used”; also, see Col 16 lines 31-39).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include displaying values of the two or more figures of merit for a selected HM configuration as taught by Coffman in order to display the two or more figures of merit as suggested by Reinhart-Wada in order to allow a user to remotely receive and visualize figures of merits such as costs and time for printing an object (see Fig. 1 and Fig. 13; also, see Col 6 lines 2-9 and Col 8 lines 59-67).
As to claim 13, this claim is the apparatus claim corresponding to the method claim 3 and is rejected for the same reasons mutatis mutandis.
Claim(s) 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Reinhart et al (US 20200264589) in view of LV et al (CN 112238603A as supported by the machine translation provided), Wada et al (JP 2005025445A as supported by the machine translation provided), Agarwal et al (US 20230211561) and Nelaturi et al (EP 3206100 A1) as applied to claim 1, and further in view of Razzell et al (US 20200265122).
As per claim 7, Reinhart-Lv-Wada-Agarwal-Nelaturi teaches the method of claim 1, while Reinhart teaches that subtractive operations/removal are performed in a printed model (0035), Reinhart-Lv-Wada-Agarwal-Nelaturi does not explicitly teach wherein the user input parameters comprise user selected portions of the 3D object that the user has identified to be machine modified in a post printing process.
However, Razzell teaches a method and system for generating a 3D object using hybrid manufacturing comprising receiving user input parameters, wherein the user input parameters comprise user selected portions of the 3D object that the user has identified to be machine modified in a post printing process (see [0059] “..the user is enabled by the UI 500 to select various surfaces of the solids 510, 512, 514, 516 where the generatively designed geometry will connect… For example, the user can specify machining tolerance values for particular surfaces of the solids 510, 512, 514, 516, these machining tolerance values can be used to determine tools and toolpaths where CNC machining will be performed, and the determined tools and toolpaths can be used to determine machining keep out regions and machining loads that are included as input to the generative design process…”; also, see [0060] and [0063] “…the design criteria can include one or more subtractive manufacturing objectives and/or constraints that affect the fixturing(s), the tool(s), the toolpath(s), or a combination thereof. For example, a machining tolerance and/or surface finish can be specified for at least a portion of the input solid(s) used for the generative design, and such manufacturing constraints can cause particular tools and forces to be applied to the workpiece to achieve the required machining tolerance and/or surface finish. For example, the specified machining tolerance and/or surface finish can require specific machining operations with tools of different shapes and sizes…”).
Therefore, it would have been obvious to one of ordinary skilled in the art before effective filing date of the claimed invention to which said subject matter pertains to have modified Reinhart’s combination as taught above to include receiving user input parameters, wherein the user input parameters comprise user selected portions of the 3D object that the user has identified to be machine modified in a post printing process as taught by Razzell in order to produce 3D object with desired characteristic in selected user’s portions (see [0063]).
As to claim 17, this claim is the apparatus claim corresponding to the method claim 7 and is rejected for the same reasons mutatis mutandis.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon, as cited in PTO form 892, is considered pertinent to applicant's disclosure.
Harris et al (US 20230088537) teaches a method and system for making a 3D object comprising computing and generating a printing configuration comprising steps/nodes that comprises values of merit such as likelihood print job failure or part failure (see 1A-1B step 192; also, see 0011, 0015-0016).
Blaier et al (US 20190366644) teaches a method and system for optimizing a design for 3D printing comprising estimating the cost of printing (see 0071).
Pluke (WO 2019180466) teaches a system and method for generating a configuration for printing a 3D object comprising generating a configuration for printing an object based on constraints, objectives, and user input, wherein the configuration comprises an orientation is determined that optimize a printing time and cost of printing (see ).
Examiner respectfully requests, in response to this Office action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line number(s) in the specification and/or drawing figure(s). This will assist Examiner in prosecuting the application.
When responding to this Office Action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the references cited or the objections made. Applicant must also show how the amendments avoid or differentiate from such references or objections. See 37 CFR 1.111 (c).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to OLVIN LOPEZ ALVAREZ whose telephone number is (571) 270-7686 and fax (571) 270-8686. The examiner can normally be reached Monday thru Friday from 9:00 A.M. to 6:00 P.M.
If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Robert Fennema, can be reached at (571) 272-2748. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/O. L./
Examiner, Art Unit 2117
/ROBERT E FENNEMA/Supervisory Patent Examiner, Art Unit 2117