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 .
Responsive to the communication dated 08/20/2025
Claims 1-7, 9-13, 15-19 are presented for examination
Information Disclosure Statement
The IDS dated 01/06/2022, 01/25/2024, 07/03/2024, and 09/10/2024 have been reviewed. They are accepted.
Drawings
The drawings dated 01/06/2022 have been reviewed. They are accepted.
Abstract
The abstract of the disclosure has been reviewed. It contains 121 words and no legal phraseology. It is accepted.
Finality
THIS ACTION IS MADE FINAL. 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 extension fee 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.
Response to Arguments -103
Applicant's arguments filed 08/20/2025 have been fully considered but they are not persuasive.
Applicant argues that none of the references teach that the system recommends that the manufacturing inputs of the digital build package be altered in such a way that an embedding corresponding to the altered digital build package is separated from the second embedding by a distance that is greater than a distance between the first embedding and the second embedding
Examiner responds by firstly explaining that, after review of the specification, particularly [Par 76], this is interpreted as having essentially the same meaning as recommending that the package be less similar to a historic version. While applicants argue that Kanthasamy “teaches away” from this, it in fact teaches it very clearly. In particular, ([Col 5 Line 51- 63] “Using inference engine 108 and knowledge base 106 (e.g., previous knowledge of objects similar to object 200), rule-based suggestion engine 100 may generate one or more suggestions to user 102 in the form of objects 210, 220, 230 of FIGS. 2B-D. For example, in FIG. 2B, rule-based suggestion engine 100 may suggest that hole 212 of object 210 be widened to reduce stress or to maximize performance. As another example, in FIG. 2C, rule-based suggestion engine 100 may suggest that hole 222 of object 220 be more rectangular to reduce stress. As yet another example, in FIG. 2D, rule-based suggestion engine 100 may suggest the creation of additional holes 232, 234 in object 230 in order to reduce stress on hole 236. Rule-based suggestion engine 100 may provide these suggestions as a result of determining that the stress on hole 202 in object 200 would be too great.”) is describing taking historic object data (“Using … knowledge base 106 (e.g., previous knowledge of objects similar to object 200),”) and current initial object data (object 200) suggestions are made to make modifications to improve it. If historical data shows that a feature of the current design makes the design worse, a recommendation is made to alter it to further move away from that design choice. To further explain, if each version of the data is associated with an embedding, as in the combination of Solidworks, Arena, Miller, Davies, and Kanthasamy, recommending that the altered data be more different from previous a previous version of the data than a current version of the data is the same thing as recommending that the distance between the embedding of the altered data and the second embedding (related to the previous design) be greater than the distance between the first embedding (related to the current design) and the second embedding.
Applicant argues that Miller teaches away from Kanthasamy
Examiner responds by firstly explaining that prior art references need not be directed to the same exact invention as the disclosure or each other to be valid references. Miller discloses a complex system for comparison between project versions, and while in the case of Miller such a system is used for the purpose of bringing newer versions that diverge more in line with previous versions, it would have been easily recognized by one of ordinary skill in the art that such a difference detection system could be readily applied to recommend that something be made more different than be made more similar. For this reason alone one of ordinary skill in the art seeking to create a system that recommends new designs be made more different than older ones would have been motivated to combine Miller with Kanthasamy.
Response to Arguments -101
Applicant's arguments filed 08/20/2025 have been fully considered but they are not persuasive.
Applicant argues that the claims are patent eligible under 101 because they provide an improvement to technology.
Examiner responds by explaining that the alleged improvement is facilitated solely by the abstract idea (to which the claims are directed), namely the mental process of analyzing old and current designs, judging how much has changed, and the human activity of recommending that the current design be modified to be more different from previous versions. The ability to observe previous versions of things, judge what worked and didn’t work, and using these insights to inform the creation of a new version is the basic concept of human invention and is a mental process. The use of digital elements and a generic machine learning model recited at a high level of generality amounts to no more than mere instructions to apply.
Further, the alleged improvement of allowing consistency across multiple uses of information/ multiple facilities is merely the act of claiming features inherent to the use of a general purpose computer in its ordinary capacity; information stored in a computer file will remain relatively consistent and retain integrity across accesses while information stored purely in the mind and relayed verbally may propagate errors and inconsistencies due to the limits of human memory.
Therefore, the claims do not provide an improvement to technology, see (MPEP 2106.05(a)(I): An inventive concept "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself." Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016))
Applicant argues that because the claims allegedly recite a “technology-based solution’ it overcomes the rejection.
Examiner responds by explaining that the citations referred to by the applicants in their arguments were found to be eligible because of their unconventionality in their additional elements; in contrast, the claims disclose a system that performs the mental process of analyzing old and current designs, judging how much has changed, and the human activity of recommending that the current design be modified to be more different from previous versions while using generic computer components recited at a high level of generality. For example, what kind of machine learning model is used or how the files are constructed is not recited in any way that suggests these elements are anything but generic. The solution comes about not as a result of a specialized technology, but as a result of abstract ideas implemented using general purpose computer components in their ordinary capacity.
Applicant argues that claims 6, 12, and 18 provide a transformation or reduction of an article to a different state or thing.
Examiner responds by explaining that in order to integrate into a practical application/provide significantly more/ provide an inventive concept, steps that do so must be particular, not be recited at a high level of generality, and have sufficient interplay between the abstract idea and the additional elements that they consist of more than insignificant post-solution activity. In contrast, there is little particularity recited in the claims in describing how the manufacturing is actually accomplished, with the specification itself describing the manufacturing process as consisting of virtually anything ([Par 19] “Information regarding the manufacturing process can include, for example: process type (e.g., injection molding, stereolithography, 3D printing, additive processes, subtractive processes, and/or the like), type of manufacturing equipment to be employed, tooling designs to be employed, process parameters (e.g., temperature, pressure, time, a combination thereof, and/or the like), process settings, process constraints, manufacturing instructions for workers and/or manufacturing equipment, a combination thereof, and/or the like.”) In such a case, this manufacturing is essentially equivalent to an abstract process of designing a hairstyle with a final step of cutting hair with the designed style. See ((MPEP 2106.05)(g)(Insignificant application) i. Cutting hair after first determining the hair style, In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016) and ii. Printing or downloading generated menus, Ameranth, 842 F.3d at 1241-42, 120 USPQ2d at 1854-55.)
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, 9-13, and 15-19 are rejected under 35 U.S.C. 101 because they are directed to an abstract idea without significantly more.
Claim 1 (Statutory Category – Machine)
Step 2A – Prong 1: Judicial Exception Recited?
Yes, the claim recites a mental process, specifically:
MPEP 2106.04(a)(2)(Ill): “Accordingly, the "mental processes" abstract idea grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, Judgments, and opinions.”
Further, the MPEP recites “The courts do not distinguish between mental processes that are performed entirely in the human mind and mental processes that require a human to use a physical aid (e.g., pen and paper or a slide rule) to perform the claim limitation.”
a similarity component that executes a trained machine learning model on the digital build package such that the trained machine learning model receives as input at least the computer-aided design file, thereby causing the trained machine learning model to produce as output a first embedding; and an insight component that: identifies an historical digital build package corresponding to a previously-manufactured product design and for which the trained machine learning model has produced a second embedding that is within a threshold distance of the first embedding;
Determining how similar two things are is a mental process equivalent to observing both items and making an arbitrary judgement about how similar they are. For example, a person could look at the blueprints for a vehicle built in 1985 and blueprints for the same model in the current year and make an arbitrary judgement of how much the design has changed (i.e. a considerable amount, not much, 10% different, etc.)
Further, identifying designs for a previous versions of something is a mental process equivalent to observing such previous designs, such as by looking through a list of various models years of vehicles found in certain mechanic’s guides that cover several revisions of a vehicle.
Additionally, determining that numeric data is within a threshold is a mental process equivalent to observing the numeric data and judging whether it is above or below the threshold value.
Doing all of this via the embeddings of a generic trained machine learning model and using ‘digital’ build packages amounts to no more than mere instructs to apply the exception on a generic computer.
The claim also recites certain methods of organizing human activity, in particular:
… recommends that the manufacturing inputs of the digital build package be altered in such a way that an embedding corresponding to the altered digital build package is separated from the second embedding by a distance that is greater than a distance between the first embedding and the second embedding.
Since every package instance (historical, current, altered) is associated with an embedding relating to its state, recommending that “the digital build package be altered in such a way that an embedding corresponding to the altered digital build package is separated from the second embedding by a distance that is greater than a distance between the first embedding and the second embedding.” Is the same as recommending that the current package be altered to be even more different from the historical package than it already is.
This is equivalent to instructing a person do something, which is explicitly recognized by the MPEP as an example of a method of organizing human activity (MPEP 2106.04(a)(2)(II) “The phrase "methods of organizing human activity" is used to describe concepts relating to: … managing personal behavior or relationships or interactions between people, (including social activities, teaching, and following rules or instructions).” MPEP 2106.04(a)(2)(II)(C) ii. considering historical usage information while inputting data, BSG Tech. LLC v. Buyseasons, Inc., 899 F.3d 1281, 1286, 127 USPQ2d 1688, 1691 (Fed. Cir. 2018) i. assigning hair designs to balance head shape, In re Brown, 645 Fed. Appx. 1014, 1015-16 (Fed. Cir. 2016) (non-precedential); and ii. a series of instructions of how to hedge risk, Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1004 (2010).)
The use of machine learning embeddings in this amounts to no more than mere instructions to apply.
Step 2A – Prong 2: Integrated into a Practical Solution?
Insignificant Extra-Solution Activity (MPEP 2106.05(g)) has found mere data gathering and
post solution activity to be insignificant extra-solution activity.
Mere Instructions to Apply (MPEP 2106.05(f)) has found that merely applying a judicial exception such as an abstract idea, as by performing it on a computer, does not integrate the claim into a practical solution.
Mere Instructions to Apply:
a build package component that canonicalizes manufacturing inputs regarding a product design into a digital build package that enables portability of manufacturing the product design within a network of manufacturing facilities, wherein the digital build package delineates how the product design is to be manufactured and references a computer-aided design file that characterizes the product design;
Packaging files into a single container file is a basic feature of most modern file systems. Should it be found that this element is not an example of mere instructions to apply, it is also well-understood, routine, conventional activity
a similarity component that executes a trained machine learning model on the digital build package such that the trained machine learning model receives as input at least the computer-aided design file, thereby causing the trained machine learning model to produce as output a first embedding; and an insight component that: identifies an historical digital build package corresponding to a previously-manufactured product design and for which the trained machine learning model has produced a second embedding that is within a threshold distance of the first embedding;
Applying a computer to perform a generic neural network operations at a high level of generality is simply the act of instructing a computer to perform generic functions to perform those operations, which is merely an instruction to apply a computer to the judicial exception. The claim only recites the idea of a solution or outcome, i.e. that the neural network is “executed” on the file to produce the embeddings without reciting how this operation is actually accomplished. Further, the computer elements claimed are cited as merely generic tools to perform the operations; for additional clarity see ([Par 67] “Example machine learning models can include, but are not limited to: perceptron (“P”), feed forward (“FF”), radial basis network (“RBF”), deep feed forward (“DFF”), recurrent neural network (“RNN”), long/short term memory (“LSTM”), gated recurrent unit (“GRU”), auto encoder (“AE”), variational AE (“VAE”), denoising AE (“DAE”), sparse AE (“SAE”), markov chain (“MC”), Hopfield network (“HN”), Boltzmann machine (“BM”), deep belief network (“DBN”), deep convolutional network (“DCN”), deconvolutional network (“DN”), deep convolutional inverse graphics network (“DCIGN”), generative adversarial network (“GAN”), liquid state machine (“LSM”), extreme learning machine (“ELM”), echo state network (“ESN”), deep residual network (“DRN”), kohonen network (“KN”), support vector machine (“SVM”), and/or neural turing machine (“NTM”). Many other types of machine learning models and methods are known to those skilled in the art and could be readily integrated into the system 100.”)
Step 2B: Claim provides an Inventive Concept?
No, as discussed with respect to Step 2A, the additional limitations are mere instructions to apply an exception and do not impose any meaningful limits on practicing the abstract idea and therefore the claim does not provide an inventive concept in Step 2B.
Mere Instructions to Apply (MPEP 2106.05(f)) has found that merely applying a judicial exception such as an abstract idea, as by performing it on a computer, does not integrate the claim into a practical solution.
Mere Instructions to Apply:
a build package component that canonicalizes manufacturing inputs regarding a product design into a digital build package that enables portability of manufacturing the product design within a network of manufacturing facilities, wherein the digital build package delineates how the product design is to be manufactured and references a computer-aided design file that characterizes the product design;
Packaging files into a single container file is a basic feature of most modern file systems. Should it be found that this element is not an example of mere instructions to apply, it is also well-understood, routine, conventional activity.
See (MPEP 2106.05(f)(2)(i)) “A commonplace business method or mathematical algorithm being applied on a general purpose computer,” [Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 573 U.S. 208, 223, 110 USPQ2d 1976, 1983 (2014); Gottschalk v. Benson, 409 U.S. 63, 64, 175 USPQ 673, 674 (1972); Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); ]
a similarity component that executes a trained machine learning model on the digital build package such that the trained machine learning model receives as input at least the computer-aided design file, thereby causing the trained machine learning model to produce as output a first embedding; and an insight component that: identifies an historical digital build package corresponding to a previously-manufactured product design and for which the trained machine learning model has produced a second embedding that is within a threshold distance of the first embedding;
Applying a computer to perform a generic neural network operations at a high level of generality is simply the act of instructing a computer to perform generic functions to perform those operations, which is merely an instruction to apply a computer to the judicial exception. The claim only recites the idea of a solution or outcome, i.e. that the neural network is “executed” on the file to produce the embeddings without reciting how this operation is actually accomplished. Further, the computer elements claimed are cited as merely generic tools to perform the operations; for additional clarity see ([Par 67] “Example machine learning models can include, but are not limited to: perceptron (“P”), feed forward (“FF”), radial basis network (“RBF”), deep feed forward (“DFF”), recurrent neural network (“RNN”), long/short term memory (“LSTM”), gated recurrent unit (“GRU”), auto encoder (“AE”), variational AE (“VAE”), denoising AE (“DAE”), sparse AE (“SAE”), markov chain (“MC”), Hopfield network (“HN”), Boltzmann machine (“BM”), deep belief network (“DBN”), deep convolutional network (“DCN”), deconvolutional network (“DN”), deep convolutional inverse graphics network (“DCIGN”), generative adversarial network (“GAN”), liquid state machine (“LSM”), extreme learning machine (“ELM”), echo state network (“ESN”), deep residual network (“DRN”), kohonen network (“KN”), support vector machine (“SVM”), and/or neural turing machine (“NTM”). Many other types of machine learning models and methods are known to those skilled in the art and could be readily integrated into the system 100.”)
The courts have found that such mere instructions to apply are not indicative of integration into a practical application nor recitation of significantly more than the judicial exception (MPEP 2106.05(f) “Another consideration when determining whether a claim integrates a judicial exception into a practical application in Step 2A Prong Two or recites significantly more than a judicial exception in Step 2B is whether the additional elements amount to more than a recitation of the words "apply it" (or an equivalent) or are more than mere instructions to implement an abstract idea or other exception on a computer. As explained by the Supreme Court, in order to make a claim directed to a judicial exception patent-eligible, the additional element or combination of elements must do "‘more than simply stat[e] the [judicial exception] while adding the words ‘apply it’". Alice Corp. v. CLS Bank, 573 U.S. 208, 221, 110 USPQ2d 1976, 1982-83 (2014) (quoting Mayo Collaborative Servs. V. Prometheus Labs., Inc., 566 U.S. 66, 72, 101 USPQ2d 1961, 1965). Thus, for example, claims that amount to nothing more than an instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1983”)
Well-Understood, Routine, Conventional Activity (WURC) has found that claim elements that are understood to be Well-Understood, Routine, Conventional Activity are not indicative of Integration into a Practical Solution nor evidence of an Inventive Concept (MPEP 2106.05(d))
WURC:
a build package component that canonicalizes manufacturing inputs regarding a product design into a digital build package that enables portability of manufacturing the product design within a network of manufacturing facilities, wherein the digital build package delineates how the product design is to be manufactured and references a computer-aided design file that characterizes the product design;
Packaging files into a single container file is a well-understood, routine, conventional activity common to most modern file systems. See the following:
How to Unzip and Zip files ([Page 1 Par 1-4])
What is file compression? ([Page 2 Par 4], [Page 3 Par 1-3])
Moreover, Mere Instructions To Apply An Exception (MPEP 2106.05(f)) has found that simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. In light of this, the additional generic computer component elements of “A system, comprising: a memory that stores computer executable components and a processor, operably coupled to the memory, and that executes the computer executable components stored in the memory, wherein the computer executable components comprise: a digital build package; executes a trained machine learning model on the digital build package; computer-aided design file; a first embedding; an historical digital build package; a second embedding ” are not sufficient to integrate a judicial exception into a practical application nor provide evidence of an inventive concept.
The additional elements have been considered both individually and as an ordered combination in the consideration of whether they constitute significantly more, and have been determined not to constitute such.
The claim is ineligible.
Claim 9 The elements of claim 9 are substantially the same as those of claim 1. Therefore, the elements of claim 9 are rejected due to the same reasons as outlined above for claim 1.
Moreover, Mere Instructions To Apply An Exception (MPEP 2106.05(f)) has found that simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. In light of this, the additional generic computer component elements of claim 9: “a system operatively coupled to a processor, a digital build package; executing, by the system, a trained machine learning model on the digital build package; computer-aided design file; a first embedding; an historical digital build package; a second embedding ” are not sufficient to integrate a judicial exception into a practical application nor provide evidence of an inventive concept.
Claim 15 The elements of claim 15 are substantially the same as those of claim 1. Therefore, the elements of claim 15 are rejected due to the same reasons as outlined above for claim 1.
Moreover, Mere Instructions To Apply An Exception (MPEP 2106.05(f)) has found that simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. In light of this, the additional generic computer component elements of claim 15: “A computer program product for assembling a build package, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to: a digital build package; execute a trained machine learning model on the digital build package; computer-aided design file; a first embedding; an historical digital build package; a second embedding ” are not sufficient to integrate a judicial exception into a practical application nor provide evidence of an inventive concept.
Further, regarding claim 15 the claim(s) are directed to a “system” or machine, but fails to disclose physical “things”. The elements of the claim are construed as software (see paragraph 6 of Specification). Products that do not have a physical or tangible form, such as information (often referred to as "data per se") or a computer program per se (often referred to as "software per se") when claimed as a product without any structural recitations are not directed to any of the statutory categories (MPEP 2106.03).
Claim 2 recites “an attribute component that generates a simplified summary that characterizes the product design by extracting a plurality of design attribute values from the computer-aided design file; and a standardization component that structures the simplified summary into an intermediate data form.”
Generating a summary of a design is a mental process that is equivalent to observing the design and coming up with an arbitrary description of it. For example a person could observe a car and write down, with a pen and paper, the description “fast, has tires, uses gas”
Converting data to another format is explicitly identified by the MPEP as an example of a mathematic process (MPEP 2106.04(a)(2)(A) ii. a conversion between binary coded decimal and pure binary, Benson, 409 U.S. at 64, 175 USPQ at 674; )
Claim 10. The elements of claim 10 are substantially the same as those of claim 2. Therefore, the elements of claim 10 are rejected due to the same reasons as outlined above for claim 2.
Claim 16. The elements of claim 16 are substantially the same as those of claim 2. Therefore, the elements of claim 16 are rejected due to the same reasons as outlined above for claim 2.
Claim 3 recites “wherein the plurality of design attribute values include a size and shape of a geometric feature of the product design.”
This merely clarifies the form of the design attributes and is therefore merely an extension of the mental process.
Claim 4 recites “a packaging component that executes a packaging algorithm to generate the digital build package based on the simplified summary of the product design and a plurality of manufacturing attribute values extracted from the manufacturing inputs.”
Packaging files into a single container file is a basic feature of most modern file systems. Should it be found that this element is not an example of mere instructions to apply, it is also well-understood, routine, conventional activity.
See the following:
How to Unzip and Zip files ([Page 1 Par 1-4])
What is file compression? ([Page 2 Par 4], [Page 3 Par 1-3])
Specifying that this is done “based on the simplified summary… and a plurality of manufacturing attribute values” merely clarifies the conditions under which the packaging is performed.
Claim 11. The elements of claim 11 are substantially the same as those of claim 4. Therefore, the elements of claim 11 are rejected due to the same reasons as outlined above for claim 4.
Claim 17. The elements of claim 17 are substantially the same as those of claim 4. Therefore, the elements of claim 17 are rejected due to the same reasons as outlined above for claim 4.
Claim 5 recites “wherein the plurality of manufacturing attribute values delineate how the product design is to be manufactured.”
This merely clarifies the purpose of the values, and is therefore merely an extension of the mental process and mere instructions to apply
Claim 6 recites “a distribution component that distributes the digital build package within the network of manufacturing facilities based on a manufacturing attribute delineated by the digital build package, wherein a manufacturing facility from the network of manufacturing facilities manufactures the product design in accordance with the digital build package.”
Distributing data over a network is explicitly recognized by the MPEP as an example of mere instructions to apply an exception (MPEP 2106.05(f)(1) iii. Wireless delivery of out-of-region broadcasting content to a cellular telephone via a network without any details of how the delivery is accomplished, Affinity Labs of Texas v. DirecTV, LLC, 838 F.3d 1253, 1262-63, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016).)
Additionally, should it be found that this is not an example of mere instructions to apply, it is also explicitly recognized as an example of well-understood, routine, conventional activity (MPEP 2106.05(d)(II) i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)
Further, manufacturing the design in such a manner recited at such a high level of generality is essentially equivalent to an abstract process of designing a hairstyle with a final step of cutting hair with the designed style. See ((MPEP 2106.05)(g)(Insignificant application) i. Cutting hair after first determining the hair style, In re Brown, 645 Fed. App'x 1014, 1016-1017 (Fed. Cir. 2016) and ii. Printing or downloading generated menus, Ameranth, 842 F.3d at 1241-42, 120 USPQ2d at 1854-55.)
Claim 12. The elements of claim 12 are substantially the same as those of claim 6. Therefore, the elements of claim 12 are rejected due to the same reasons as outlined above for claim 6.
Claim 18. The elements of claim 18 are substantially the same as those of claim 6. Therefore, the elements of claim 18 are rejected due to the same reasons as outlined above for claim 6.
Claim 7 recites “a version component that tracks changes to the digital build package, wherein the changes are made during a development or manufacturing of the product design, and wherein the version component generates a design history associated with the product design that comprises multiple versions of the digital build package.”
Tracking the history of a design change is a mental process equivalent to writing down each change that is made to a design, as with a pencil and paper. This written history could further include different versions of the design, for example drawn blueprints before and after a change is made.
Keeping this kind of record digitally is further explicitly identified by the courts as an example of well-understood, routine, conventional activity (MPEP 2106.05(d)(II) iii. Electronic recordkeeping, Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 225, 110 USPQ2d 1984 (2014) (creating and maintaining "shadow accounts"); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log))
Claim 13. The elements of claim 13 are substantially the same as those of claim 7. Therefore, the elements of claim 13 are rejected due to the same reasons as outlined above for claim 7.
Claim 19. The elements of claim 19 are substantially the same as those of claim 7. Therefore, the elements of claim 19 are rejected due to the same reasons as outlined above for claim 7.
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.
Claims 1-7, 9-13, and 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over Mastering Solidworks: The Design Approach (Hereinafter Solidworks) in view of Arena PDXViewer (Hereinafter Arena) in further view of Miller (US20220066415A1) as well as Davies (US 20200134909 A1) and Kanthasamy (US 10013510 B1)
Claim 1.Solidworks makes obvious a memory that stores computer executable components; and a processor, operably coupled to the memory, and that executes the computer executable components stored in the memory, wherein the computer executable components comprise: ([Page 6 Par 3] “ Unless you are running a 32-bit version of the Windows operating system (OS), you should install the 64-bit version of SolidWorks. Click the following sequence to find the Windows version you are running:…”) ([Page 135 Fig 4.29] Shows models of product designs)
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([Page 146 Par 2] “A BOM is usually used in assembly drawings. It typically shows the part number, how many instances of the part are used in the assembly, and what its material is” [Page 425 Par 6 – 426 Par 4] “3. Generate the build file: The RP machine software reads the STL file and displays the model… After setting up the model orientation, we select the slicing thickness (layer resolution). The RP software allows us to select from a recommended resolution list because the slice thickness is determined based on the RP machine build accuracy, the build material, and other factors… We then select the style of the support structure (break-away, sparse, or other type). The output from the software is a proprietary build file that the RP machine reads to build the prototype. 4. Build the bottle prototype: Start the machine to build. Make sure there are enough build and support materials. The machine builds and does not have to be attended during build.”) and references a computer-aided design file that characterizes the product design. ([Page 400 Par 1-2] “The theme for the tutorials in this chapter is to practice the different analysis tools covered in this chapter including exporting CAD models, performing mass property calculations, motion analysis, flow analysis, stress FEM/FEA, and thermal FEM/FEA… We export a native SolidWorks file in both IGES and STEP formats.” [Page 400 Col 2 Par 2] “Step 3: Save part as STEP file: File > Save as > block > STEP AP203 from the Save as type drop-down > Save.”) ([Page 400 Par 1-2] “The theme for the tutorials in this chapter is to practice the different analysis tools covered in this chapter including exporting CAD models, performing mass property calculations, motion analysis, flow analysis, stress FEM/FEA, and thermal FEM/FEA… We export a native SolidWorks file in both IGES and STEP formats.” [Page 400 Col 2 Par 2] “Step 3: Save part as STEP file: File > Save as > block > STEP AP203 from the Save as type drop-down > Save.”) ([Page 426 Fig 14.10] Shows a product design for a bottle after being manufactured, i.e. a previously-manufactured product design)
Solidworks fails to make obvious a build package component that canonicalizes manufacturing data regarding a product design into a digital build package that enables portability of manufacturing the product design within a network of manufacturing facilities, wherein the digital build package contains manufacturing data; a similarity component that executes a trained machine learning model on the digital build package such that the trained machine learning model receives as input design data, thereby causing the trained machine learning model to produce as output a first embedding; and an insight component that: identifies an historical digital build package corresponding to a previous version and for which the trained machine learning model has produced a second embedding that is within a threshold distance of the first embedding; and recommends that the manufacturing inputs of the digital build package be altered in such a way that an embedding corresponding to the altered digital build package is separated from the second embedding by a distance that is greater than a distance between the first embedding and the second embedding.
Arena makes obvious a build package component that canonicalizes manufacturing data regarding a product design into a digital build package that enables portability of manufacturing the product design within ([Page 2 Col 1 Par 1] “ PDX is commonly used throughout design and supply chains to capture and share associated approved manufacturing lists (AMLs),change history and design files in a single package” [Page 2 Col 1 Par 3] “ PDX files let manufacturers zip and send detailed BOM, prints, specs, other files, a traveler/router, and/or a message explaining what has been sent to anyone, anywhere on the planet.” [Examiner’s note: zipping a set of files involves packaging the multiple files into a single container file and compressing them, producing a single unified, reduced file with data in a standardized form] [Page 2 Col 1 Par 4] “Using the PDX File Standard PDX files take seconds to create, and are the cleanest and most secure way for OEMs and suppliers to share build kits, BOM data and quote packages” [Page 2 Col 2 Par 1-2] “Both original equipment manufacturers (OEMs) and contract manufacturers (CMs) use PDX files to exchange complex product data between PLM and ERP systems throughout the manufacturing process. On the OEM side, operations, document control, purchasing and supply chain managers use PDX files to cleanly exchange read-only data with suppliers. On the contract manufacturer side, program managers create and view PDX files for unequivocal and unambiguosly clean hand-offs provided by the format.”) ([Page 2 Col 1 Par 1] “ PDX is commonly used throughout design and supply chains to capture and share associated approved manufacturing lists (AMLs),change history and design files in a single package”) ([Page 2 Col 1 Par 2] “PDX is commonly used throughout design and supply chains to capture and share associated approved manufacturing lists (AMLs), change history and design files in a single package”[Page 3] Clearly shows a “Change History” Menu tab containing historical versions of the package and component ) ([Page 2 Col 1 Par 1] “ PDX is commonly used throughout design and supply chains to capture and share associated approved manufacturing lists (AMLs),change history and design files in a single package”) ([Page 2 Col 1 Par 1] “ PDX is commonly used throughout design and supply chains to capture and share associated approved manufacturing lists (AMLs),change history and design files in a single package”)
Arena is analogous art because it is within the field of generating digital build packages for use with manufacturing. It would have been obvious to combine it with Solidworks before the effective filing date.
One of ordinary skill in the art would have been motivated to make this combination to allow for greater portability and shareability of manufacturing projections, allowing significantly improved collaboration between designers and manufacturers. While Solidworks is an extremely powerful design platform that does incorporate some features to simplify collaboration, such as the ability to export solidworks projects as files ([Page 400 Par 1-2] “The theme for the tutorials in this chapter is to practice the different analysis tools covered in this chapter including exporting CAD models, performing mass property calculations, motion analysis, flow analysis, stress FEM/FEA, and thermal FEM/FEA… We export a native SolidWorks file in both IGES and STEP formats.” [Page 400 Col 2 Par 2] “Step 3: Save part as STEP file: File > Save as > block > STEP AP203 from the Save as type drop-down > Save.”) Solidworks lacks a comprehensive mechanism for collecting models, official documents, cost analyses, notes, high level specifications, product images, and other information essential to a manufacturing process into a single package that can be easily shared to give a manufacturer or collaborator everything they need to start production. To this end, Arena presents their PDXviewer product and its associated PDX file standard that allows packaging all the information required to manufacture a product, from digital models to cost quotes, product images, and notes into a single file that can be easily and securely shared with anyone. ([Page 2 Col 1 Par 3] “ PDX files let manufacturers zip and send detailed BOM, prints, specs, other files, a traveler/router, and/or a message explaining what has been sent to anyone, anywhere on the planet.” [Page 2 Col 1 Par 4] “PDX files take seconds to create, and are the cleanest and most secure way for OEMs and suppliers to share build kits, BOM data and quote packages” [Page 2 Col 2 Par 2] “On the OEM side, operations, document control, purchasing and supply chain managers use PDX files to cleanly exchange read-only data with suppliers. On the contract manufacturer side, program managers create and view PDX files for unequivocal and unambiguosly clean hand-offs provided by the format.”) Overall, one of ordinary skill in the art would have recognized that combining Solidworks with Arena would allow more effective communication and collaboration between designers, contractors, manufacturers, and all other parties involved in a manufacturing process, allowing large-scale manufacturing operations to run more smoothly and efficiently at all points along the supply chain.
The combination of Solidworks and Arena fails to make obvious a network of manufacturing facilities; a similarity component that executes a trained machine learning model on design data such that the trained machine learning model receives as input design data, thereby causing the trained machine learning model to produce as output a first embedding; and an insight component that: takes a historical version of data corresponding to a previously version and for which the trained machine learning model has produced a second embedding that is within a threshold distance of the first embedding; and recommends that the manufacturing inputs of the current data be altered in such a way that an embedding corresponding to the altered data is separated from the second embedding by a distance that is greater than a distance between the first embedding and the second embedding.
Miller makes obvious a network of manufacturing facilities ([Par 26] “The components may communicate via local and/or remote processes such as in accordance with a signal having one or more data packets (e.g., data from one component interacting with another component in a local system, distributed system, and/or across a network such as the Internet with other systems via the signal)” [Par 95] “ By allowing multiple versions of a control project to be archived in the customer repository 324 and deployed to the plant floor devices on demand, the repository system's storage and deployment features can allow users to deploy different versions of the same control project at different industrial facilities.”) and ([Par 62] “the project generation component 206 can identify whether the control programming being submitted as part of design input 404 deviates from either the plant's preferred coding practices or the plant's preferred manner of controlling certain industrial operations based on comparison with the project versions 310, and generate design feedback 406 notifying of these deviations and recommending alternative control coding that will bring the current project into conformity with previous design strategies”) ([Par 3] “a project analysis component configured to perform a second analysis on the project telemetry data and to generate, based on a result of the second analysis, a recommendation for modifying the industrial control project in a manner that improves one or more of the predicted operating characteristics,” [Par 96] “For example, when a new version of a control project 306 is submitted, asset recovery component 214 can compare this new version with one or more previous project versions 310 previously submitted to and archived by the repository system 202. If this comparison yields a determination that the new version is drastically different from previous versions 310…” [Par 60] “Project generation component 206 can monitor the design input 404 with reference to the functional project requirements defined by the plant standards 314 and, upon determining that any portion of the submitted design input 404 deviates from the defined functional specifications or safety validation requirements, generate design feedback notifying the user of the deviation and offering recommendations as to how the deviant portion of the control project can be brought within compliance. Plant standards 314 can define functional specifications in terms of manufacturing functions to be carried out, preferred equipment vendors,” [Par 62] “the project generation component 206 can identify whether the control programming being submitted as part of design input 404 deviates from either the plant's preferred coding practices or the plant's preferred manner of controlling certain industrial operations based on comparison with the project versions 310, and generate design feedback 406 notifying of these deviations and recommending alternative control…”)
Miller is analogous art because it is within the field of manufacturing process optimization. It would have been obvious to combine it with Solidworks and Arena before the effective filing date.
One of ordinary skill in the art would have been motivated to make this combination in order to optimize the manufacturing process by providing dynamic modification recommendations to further enhance production capabilities. Manually optimizing a manufacturing process can be very time and labor-intensive, making improvement progress slow. Further, the right direction to go in order to reach a desired improvement may not be clear, causing a designer to resort to blind, tedious methods such as trial and error. With this in mind, it would have been obvious to one of ordinary skill in the art that a method to automatically determine the best course of action to improve a manufacturing process would be an invaluable tool for optimizing the entire production operation. To this end, Miller presents a machine learning-powered system capable of analyzing the current state of a processing operation, such as a manufacturing supply chain, and dynamically suggesting modifications to improve the operation.([Par 3] “a system for analyzing industrial control projects is provided, comprising a user interface component configured to receive, from a client device via a cloud platform, an industrial control project comprising at least control programming and device configuration data that, in response to execution on one or more industrial devices, facilitate monitoring and control of an industrial automation system; a project telemetry component configured to generate project telemetry data based on a first analysis of the industrial control project, the project telemetry data defi