DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1-20 are rejected under 35 U.S.C. 101.
Claims 1-20 are rejected on the grounds of non-statutory double patenting.
Claims 3-5, 7, 15-16, and 19-20 are objected to for minor informalities.
Claims 1, 10-13, and 17 are rejected under 35 U.S.C. 103.
Claim Objections
Claims 3-5, 7, 15-16, and 19-20 are objected to because of the following informalities:
Claim 3 recites “the model”. The model appears to refer to the “Multiple Criteria Decision Aiding sorting model” recited in claim 2. For clarity, claim 3 should at least recite “the sorting model”. The same applies to claims 15 and 19.
Claim 4 recites “wherein the model includes”. The model appears to refer to the “Multiple Criteria Decision Aiding sorting model” recited in claim 2. For clarity, claim 4 should at least recite “wherein the sorting model includes”. The same applies to claims 16 and 20.
Claim 5 recites “SAT-based encoding”. Acronyms should be defined within the claim for clarity. Claim 5 should be amended to recite “satisfiability (SAT)-based encoding”.
Claim 7 recites “MaxSAT-based encoding”. Acronyms should be defined within the claim for clarity. Claim 7 should be amended to recite “maximum satisfiability (MaxSAT)-based encoding”.
Appropriate correction is required.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 1-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claims 1-20 of copending Application No. 18/358,830 (hereinafter ‘830) in view of KUMAR (US 2022/0398365 A1).
Although the claims at issue are not identical, they are not patentably distinct from each other because the claims of the instant application are recited by or obvious over the claims of ‘830. See the table comparing the limitations from the claims below.
This is a provisional nonstatutory double patenting rejection because the patentably indistinct claims have not in fact been patented.
Claims of Instant Application
Claims of ‘830
Comments
(Claim 1) A computer-implemented method for selecting materials of components of a product to be manufactured, the method comprising:
(claim 1) A computer-implemented method for designing a manufacturing product
Selecting materials for components of a product is narrower than “designing a manufacturing product”. However, a person of ordinary skill in the art would have considered selection of materials a part of a design process.
obtaining: a set of materials for the components of the product…
obtaining a set of materials for manufacturing the product
Substantially similar.
for the product: a set of use and/or manufacturing constraints for the product; and one or more material compatibility constraints;
obtaining a set of use and/or manufacturing constraints for the manufacturing product;
Underlined portion not included in claim 1 of the instant application.
and specifications indicating an extent of compatibility of one or more reference materials within the set of materials with the constraints;
obtaining specifications indicating an extent of compatibility of one or more reference materials with the constraints;
Substantially Similar
and determining, for each component of the product, at least one optimal material, with respect to compatibility with the constraints and based on the obtained specifications, for manufacturing the component.
and determining an optimal subset of the set of materials for manufacturing the product, the determining including classifying the materials with respect to compatibility with the constraints and based on the obtained specifications.
Substantially Similar.
Similar comparisons can be made between claims 13 and 17 of the instant application and ‘830.
(Claim 2) wherein the determining of the optimal materials for the components further comprises learning a Multiple Criteria Decision Aiding sorting model configured to take as input the set of materials and to output the optimal materials for the components, the learning being based on the set of materials, on the constraints, and on the specifications.
(claim 2) wherein the classification including learning a Multiple Criteria Decision Aiding sorting model configured to take as input a set of materials and to output an optimal subset of materials, the learning being based on the set of materials, on the constraints, and on the specifications.
Substantially Similar. The same applies to claims 14 and 18 of the instant application and ‘830.
(Claim 3) wherein the specifications form a learning set of the model.
(claim 3) wherein the specifications form a learning set of the model
Identical. The same applies to claims 15 and 19 of the instant application and ‘830.
(Claim 4) wherein the model includes one or more Non-Compensatory Sorting (NCS) models.
(claim 4) wherein the model includes one or more Non-Compensatory Sorting (NCS) models.
Identical. The same applies to claims 16 and 20 of the instant application and ‘830.
(Claim 5) wherein the learning further comprises encoding learning clauses based on the constraints, the encoding using a SAT-based encoding.
(claim 5) wherein the learning includes encoding learning clauses based on the constraints, the encoding using a SAT-based encoding.
Identical
(Claim 6) wherein the specifications include incompatible specifications, and the learning includes finding a compromise between the incompatible specifications.
(claim 6) wherein the specifications include incompatible specifications, and the learning includes finding a compromise between the incompatible specifications.
Identical
(Claim 7) wherein the learning further comprises encoding learning clauses based on the constraints, the encoding using a MaxSAT-based encoding.
(claim 7) wherein the learning includes encoding learning clauses based on the constraints, the encoding using a MaxSAT- based encoding.
Identical
(Claim 8) wherein finding a compromise further comprises iteratively modifying the learning set until reaching an extent of compatibility between the specifications.
(claim 8) wherein finding a compromise includes iteratively modifying the learning set until reaching an extent of compatibility between the specifications.
Identical
(Claim 9) wherein the incompatible specifications are obtained by different users.
(claim 9) wherein the incompatible specifications are obtaining from different users.
Identical
(Claim 10) wherein the specifications are obtained by one or more users.
(claim 10) wherein the specifications are obtained from one or more users.
Identical
(Claim 11) wherein one or more constraints are latent constraints.
(claim 11) wherein one or more constraints are latent constraints.
Identical
(Claim 12) wherein the method further comprises using the determined at least one optimal material for manufacturing the components.
(claim 12) further comprising: selecting one or more materials within the determined optimal subset; and using the selected one or more materials for manufacturing the product.
Underlined portions substantially similar.
Claim 1 of ‘830 does not recite for each component: a set of use and/or manufacturing and/or material constraints for the component; for the product… one or more material compatibility constraints
However, KUMAR, which is similarly directed to selecting optimal materials for a product, teaches for each component: a set of use and/or manufacturing and/or material constraints for the component; for the product… one or more material compatibility constraints (¶ 20, 37-39, 48, 84: Information, including characteristics and constraints (namely, “capabilities”, “features”, and “cost”), are obtained for each component part of a product being manufactured and a candidate material to be included in a bill of materials is selected based on correlation coefficients between the part and the specifications for the product. Information that is obtained includes “component compatibility”, such as the type or family of the components and the products they work in, and tolerance levels for dimensions of a component or product.)
Before the effective filing date of the invention, it would have been obvious to one
of ordinary skill in the art to modify the determination or selection of an optimal material for manufacturing a product or component of a product taught by claim 1 of ‘830 by including obtaining constraint information for each component part of the product and material compatibility constraints for the product as taught by KUMAR in order to determine an optimal bill of materials for manufacturing the product. Since the references are similarly directed to selecting optimal materials for manufacturing a product, the combination would have yielded predictable results that would have amounted to performing the process for each component part of a product, including obtaining the constraint information for each part. Furthermore, KUMAR (¶ 2-3) teaches that such a method would be more exhaustive, leading to more optimal design in terms of cost, fit, and function of the designed products, which may have initially been overlooked, thus aiding the designer of the product.
Claims 13 and 17 recite the same limitations as claim 1 of the instant application and are rejected for the same reasoning over claims 13 and 17 of ‘830.
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 an abstract idea without significantly more.
Broadest Reasonable Interpretation of the Claims
The broadest reasonable interpretation of claims 1, 13, and 17 are computer methods, devices, or systems that implement a method
for selecting materials of components of a product to be manufactured, the method comprising: (A method for a user or a person implementing a manufacturing process where materials of components of a product need to be selected.)
obtaining: a set of materials for the components of the product; (The user can reference a list of candidate materials for the components of a product.)
(obtaining) for each component: a set of use and/or manufacturing and/or material constraints for the component; (The user can read or otherwise obtain the constraints for each component.)
(obtaining) for the product: a set of use and/or manufacturing constraints for the product; and one or more material compatibility constraints; (The user can read or otherwise obtain the constraints for the product, including material compatibility.)
(obtaining) and specifications indicating an extent of compatibility of one or more reference materials within the set of materials with the constraints; (The user can read or otherwise obtain specification indicating an extent of compatibility of a reference material with the constraints. For example, there can be a rating system using any type of scale or there can be any other type of quantitative or qualitative indicator that indicates the compatibility of the reference materials with the previously obtained constraints.)
and determining, for each component of the product, at least one optimal material, with respect to compatibility with the constraints and based on the obtained specifications, for manufacturing the component. (The user can then select, using the information they obtained, a material for each component of the product they are manufacturing.)
Step 1: Is the claim directed to one of the four statutory categories?
Claim 1 is directed to a process.
Claim 13 is directed to an article of manufacture that implements a process.
Claim 17 is directed to a machine that implements a process.
Step 2A Prong 1: Does the Claim recite an abstract idea?
As discussed in the claim interpretation section above, claim 1 as a whole recites an abstract idea, as every limitation is directed to the abstract idea. Namely, the independent claims recite an abstract idea of selecting optimal materials for components of a target product based on various constraints and specifications desired for the product. This is a mental process capable of being performed in the human mind, with or without a physical aide, such as pencil and paper, and is thus an abstract idea. See MPEP 2106.04(a)(2).III, including sections B-D. Since the BRI of the claims is capable of being performed in the human mind, the claims still recite a mental process despite the preambles of claims 1, 13 and 17 reciting generic computer components. MPEP 2106.04(a)(2).III.C. The “determining” step can be construed as a mathematical calculation, namely some sort of optimization problem, which is also an abstract idea. See MPEP 2106.04(a)(2).I.C.
Step 2A Prong 2: Does the claim recite additional elements that integrate the abstract idea into a practical application?
The independent claims do not recite any additional limitations and therefore do not recite any limitations that can integrate the claim as a whole into a practical application.
Step 2B: Does the claim recite additional elements that amount to significantly more than the judicial exception?
The independent claims do not recite any additional limitations and therefore do not recite any limitations that can amount to significantly more than the judicial exception.
Dependent Claims
Claims 2, 14, and 18 recite wherein the determining of the optimal materials for the components further comprises learning a Multiple Criteria Decision Aiding sorting model configured to take as input the set of materials and to output the optimal materials for the components, the learning being based on the set of materials, on the constraints, and on the specifications.
This limitation further limits the “determining” step to include a certain type of optimization algorithm, namely a Multiple Criteria Decision Aiding sorting model. However, as discussed above, this is still directed to the abstract idea and can be construed as a mathematical calculation. The claim does not recite the Multiple Criteria Decision Aiding sorting model with enough detail or with additional limitations that can be considered to integrate the abstract idea into a practical application or that can be considered significantly more.
Claims 3, 15, and 19 recite wherein the specifications form a learning set of the model.
This limitation merely limits how the model is generated and is still directed to the abstract idea recited in claim 2. The model having a particular learning set can also be considered pre-solution activity. See MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated”.
Claims 4, 16, and 20 recite wherein the model includes one or more Non-Compensatory Sorting (NCS) models.
This limitation merely limits how the model is generated, i.e. what types of models the sorting model comprises, and is still directed to the abstract idea recited in claim 2.
Claims 5 recites wherein the learning further comprises encoding learning clauses based on the constraints, the encoding using a SAT-based encoding.
This limitation merely limits how the model is generated and is still directed to the abstract idea recited in claim 2. The model using a particular type of encoding during learning can also be considered pre-solution activity. See MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated”.
Claims 6 recites wherein the specifications include incompatible specifications, and the learning includes finding a compromise between the incompatible specifications.
This limitation merely limits how the model is generated and is still directed to the abstract idea recited in claim 2. The model using particular types of specifications during learning can also be considered pre-solution activity. See MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated”.
Claims 7 recites wherein the learning further comprises encoding learning clauses based on the constraints, the encoding using a MaxSAT-based encoding.
This limitation merely limits how the model is generated and is still directed to the abstract idea recited in claim 2. The model using a particular type of encoding during learning can also be considered pre-solution activity. See MPEP 2106.05(g), “selecting a particular data source or type of data to be manipulated”.
Claims 8 recites wherein finding a compromise further comprises iteratively modifying the learning set until reaching an extent of compatibility between the specifications.
This limitation merely recites manually modifying the learning set until a desired compatibility metric is reached and is still directed to the abstract idea recited in claim 2. This manual operation can also be considered pre-solution activity. See MPEP 2106.05(g). Also see MPEP 2106.05(d), “performing repetitive calculations”.
Claims 9 recites wherein the incompatible specifications are obtained by different users.
This limitation merely recites how the specifications for the materials are obtained and is therefore pre-solution activity. See MPEP 2106.05(g), “mere data gathering”. The specifications being obtained from a plurality of users does not integrate the abstract idea into a practical application. The specifications being obtained from a plurality of users also does not amount to significantly more, as obtaining information from a plurality of users is conventional and routine. See MPEP 2106.05(d), “Storing and retrieving information in memory”, “Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Claims 10 recites wherein the specifications are obtained by one or more users.
This limitation merely recites how the specifications for the materials are obtained and is therefore pre-solution activity. See MPEP 2106.05(g), “mere data gathering”. The specifications being obtained from a plurality of users does not integrate the abstract idea into a practical application. The specifications being obtained from a plurality of users also does not amount to significantly more, as obtaining information from a plurality of users is conventional and routine. See MPEP 2106.05(d), “Storing and retrieving information in memory”, “Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Claims 11 recites wherein one or more constraints are latent constraints.
This limitation merely limits the types of constraints to a particular type of constraint, i.e. latent constraints, and is still directed to the abstract idea recited in claim 1.
Claims 12 recites wherein the method further comprises using the determined at least one optimal material for manufacturing the components.
This limitation does not integrate the abstract idea into a practical application or amount to significantly more because it is a mere instruction to apply the result of the mental process. See MPEP 2106.05(f). The claim lacks enough details that could amount to more than a generic instruction to apply the solution of the abstract idea.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 10-13, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over YUAN (US 2020/0401113 A1) in view of KUMAR (US 2022/0398365 A1).
Regarding Claim 1, YUAN teaches a computer-implemented method for selecting materials of components of a product to be manufactured, the method comprising: (¶ 15: “Some implementations herein are directed to techniques and arrangements for automatically determining a material and/or manufacturing process that includes employing machine learning and/or computer simulation for determining an optimal material and/or optimal manufacturing process for producing a product”)
obtaining: a set of materials for the components of the product… (¶ 30, 37, 44, 63: A set of materials for a product, including components of the product (see ¶ 36), is obtained from a plurality of manufacturers.)
for the product: a set of use and/or manufacturing constraints for the product; and one or more material compatibility constraints; (¶ 42, 62, 69-70, 79, Fig. 2: “Proposed material type and properties” and “proposed manufacturing process” are “use constraints” and “manufacturing constraints”. The “performance requirements” are material compatibility constraints, as the material is being selected to meet a plurality of requirements, such as those shown in Figs. 5-6 and 8-9.)
and specifications indicating an extent of compatibility of one or more reference materials within the set of materials with the constraints; (¶ 30, 37, 85-87, Fig. 8: Specifications of reference materials within a set of candidate materials are accesses and compared to the constraints selected by the user to determine an extent of compatibility (namely, a quality score) of the reference material with the constraints.)
and determining, for each component of the product, at least one optimal material, with respect to compatibility with the constraints and based on the obtained specifications, for manufacturing the component. (¶ 47-48, 71, 88-89: Using simulation models and machine learning models, one or more optimal materials for a product or component of a product that satisfy the constraints indicated by a user are selected and provided to the user.)
While YUAN teaches obtaining a plurality of constraints specified by a user, the constraints are not for each component of a product. YUAN does not explicitly teach obtaining… for each component: a set of use and/or manufacturing and/or material constraints for the component;
However, KUMAR, which is similarly directed to optimizing a manufacturing process, teaches obtaining… for each component: a set of use and/or manufacturing and/or material constraints for the component; (¶ 20, 37-39, 48, 84: Information, including characteristics and constraints (namely, “capabilities”, “features”, and “cost”), are obtained for each component part of a product being manufactured and a candidate material to be included in a bill of materials is selected based on correlation coefficients between the part and the specifications for the product.)
Before the effective filing date of the invention, it would have been obvious to one
of ordinary skill in the art to modify the selection of an optimal material for manufacturing a product or component of a product taught by YUAN by including obtaining constraint information for each component part of the product as taught by KUMAR in order to determine an optimal bill of materials for manufacturing the product. Since the references are similarly directed to selecting optimal materials for manufacturing a product, the combination would have yielded predictable results that would have amounted to performing the process for each component part of a product, including obtaining the constraint information for each part. Furthermore, KUMAR (¶ 2-3) teaches that such a method would be more exhaustive, leading to more optimal design in terms of cost, fit, and function of the designed products, which may have initially been overlooked, thus aiding the designer of the product.
Claim 13 is directed to a non-transitory computer-readable data storage medium and Claim 17 is directed to a computer system, but they otherwise recite the same limitations as claim 1. Claim 13 and Claim 17 are therefore rejected for the same reasoning discussed above.
Regarding Claim 10, YUAN in view of KUMAR further teaches wherein the specifications are obtained by one or more users. (YUAN, ¶ 16, 18, 30, 82: The specification are obtained by a plurality of suppliers or manufacturers, which are users of the system.)
Regarding Claim 11, YUAN in view of KUMAR further teaches wherein one or more constraints are latent constraints. (YUAN, ¶ 76, Fig. 5: Constraints include latent properties of a material, such as the life of the material, hardness, and yield strength.)
Regarding Claim 12, YUAN in view of KUMAR further teaches wherein the method further comprises using the determined at least one optimal material for manufacturing the components. (YUAN, ¶ 38, 50: The optimal material that is selected is sent to a manufacturing device that uses the selected material in a manufacturing process.)
Allowable Subject Matter
Claims 2-9, 14-16, and 18-20 contain allowable subject matter over the prior art but remain rejected under 35 U.S.C. 101 and due to non-statutory double patenting.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Okunev (US 2022/0036273 A1) teaches multi-criteria decision making related to product lifecycle, such as reusing components of a product in subsequent manufacturing. (¶ 8, 14, 64, Fig. 4)
Haga (US 2013/0290351 A1) teaches a search apparatus that accepts constraints and determines a level of satisfaction for a material used in manufacturing a product. (Figs. 4-5)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAMI RAFAT OKASHA whose telephone number is (571)272-0675. The examiner can normally be reached M-F 10-6 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, SCOTT BADERMAN can be reached at (571) 272-3644. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RAMI R OKASHA/Primary Examiner, Art Unit 2118
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