DETAILED ACTION
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicants’ submission filed on 03/12/2026 has been entered.
Receipt of Applicant’s amendment filed 3/12/2026 is acknowledged.
Claims 1, 3, 10, and 12 have been amended.
Claims 1-10 and 12 are pending.
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 .
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. JP2019-187627, filed on 10/11/2019.
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the
references as applied to the claims below for the convenience of the applicant. Although
the specified citations are representative of the teachings in the art and are applied to
the specific limitations within the individual claim, other passages and figures may apply
as well. Examiner may also include cited interpretations encompassed within parenthesis, e.g. (Examiner’s interpretation), for clarity. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. The entire reference is considered to provide disclosure relating to the claimed invention. The claims & only the claims form the metes & bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent & spirit of compact prosecution.
Response to Arguments
Claim Rejections under 35 U.S.C. § 112(b):
Acknowledgement is made of amended claim 3 to provide limitation clarification. Previous rejection to claim 3 due to lack of clarity is withdrawn.
Claim Rejections under 35 U.S.C. § 101:
Acknowledgement is made of amended claims 1, 3, 10 and 12.
Amendments overcome previous software per se rejections. Rejections to claims 1-9 as software per se are withdrawn.
However, amendments to claims are inefficient to overcome non-software per se rejections. Rejections to claims 1-10 and 12 are maintained. See Claim Rejections – 35 USC §101 section below.
Applicant argues amended claims are not directed to a judicial exception under Step 2A Prong 1 of the Office’s eligibility framework since they (i.e. amended claims) require “specific computational operations and data transforms”. The Examiner respectfully disagrees. As can be seen in Claim Rejections – 35 USC §101 section below, the independent claims are directed towards Mental Processes performed on a computer and/or Mathematical Concepts per MPEP 2106.04(a)(2)(I)/(III). Per MPEP 2106.04(a)(2)(III), “[t]he 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 [ ] Nor do the courts distinguish between claims that recite mental processes performed by humans and claims that recite mental processes performed on a computer.” Thus, Applicant’s argument not persuasive.
Applicant also argues amended claims integrate into a practical application under Step 2A Prong 2 of the Office’s eligibility framework since the claims are “now an ordered combination [ ] directed to a specific improvement in CAD-based automatic rule checking”, i.e. a “concrete technique that reduces noise”. After careful reconsideration, the Examiner respectfully disagrees for at least the following reasons. The steps of the subject matter eligibility analysis for products and processes that are to be used during examination for evaluating whether a claim is drawn to patent-eligible subject matter is the following:
Step 1: Determine if the claim is directed to a process, machine, manufacture, or composition of matter. Claims 1-9 are directed towards a device, therefore fall within the statutory category of a machine. Claim 10 is directed to a method, therefore falls within the statutory category of a process. And Claim 12 is directed to a non-transitory CRM, therefore falls within the statutory category of manufacture.
Step 2A (Prong 1): Determine if the claim is directed to a law of nature, a natural phenomenon (product of nature), or an abstract idea. Independent claims 1, 10, and 12 are all directed towards an abstract idea (mental processes and/or mathematical concepts) – see 35 USC §101 analysis below.
Step 2A (Prong 2)/Step 2B: Determine if the claim recites additional elements that amount to significantly more than the judicial exception. As shown in 35 USC §101 analysis section below, the additional elements as described in Step 2A Prong 2 are not sufficient to amount to significantly more than the judicial exception because the additional limitations are considered Mere Instructions to Apply an Exception and/or Field of Use and Technological Environment per MPEP 2106.05(f)/(h). Per MPEP 2106.05(f), “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. The identified additional elements are directed towards implementing an abstract idea (i.e. mental process/mathematical conepts) or other exception on a generic computer. Per MPEP 2106.05(h), “[a]nother consideration when determining whether a claim integrates the 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 generally linking the use of a judicial exception to a particular technological environment or field of use [ ] [e]xamples of limitations that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception include: iv. Specifying that the abstract idea of monitoring audit log data relates to transactions or activities that are executed in a computer environment, because this requirement merely limits the claims to the computer field”. Thus, Applicant’s argument not persuasive.
Claim Rejections under 35 U.S.C. § 103:
Acknowledgement is made of amended claims 1, 3, 10 and 12. Applicant’s arguments have been fully considered, however new grounds of rejection necessitated by amendment are presented. Rejections to claims 1-10 and 12 remain. See Claim Rejections – 35 USC §103 section below.
Applicant argues the Itabayashi-Harigai combination, as well as Tsuyoshi and Souza, (Office Action (OA) dated 12/12/2025 prior art references) do not disclose nor suggest amended features. New grounds of rejection necessitated by amendments are presented – see Itabayashi in view of Hariya (OA dated 12/12/2025 prior art of record and not relied upon) in view of Lu in Claim Rejections – 35 USC §103 section below. Thus, Applicant’s argument not persuasive.
Applicants’ argument regarding claims 6 and 9 are moot given new grounds of rejection.
Claim Interpretation
Independent claims 1, 10, and 12 recite ”(i) a geometric shape recognition function database storing a plurality of procedure functions to recognize geometric shapes included in the CAD model”. Examiner interprets “to recognize geometric shapes included in the CAD model” as intended use/purpose of the procedure functions and thus not given patentable weight.
Independent claims 1, 10, and 12 recite ”invokes the feature value recognition section to reduce the noise”. Examiner interprets “to reduce the noise” as intended use/purpose of the procedure functions and thus not given patentable weight.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 10, and 12 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description and enablement requirements. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention. The claim(s) also contains subject matter which was not described in the specification in such a way as to enable one skilled in the art to which it pertains, or with which it is most nearly connected, to make and/or use the invention.
The claims recite “determining an amount of noise using a precision-and-recall evaluation”, however Applicant fails to specifically disclose what a precision-and-recall evaluation is and how one of ordinary skill in the art would use such an evaluation to determine an amount of noise. Applicant may overcome rejections by amending claims accordingly or by showing where a precision-and-recall evaluation is disclosed and described in such a way that enables one of ordinary skill in the art to make/use the claimed invention.
The dependent claims 2-9, included in the statement of rejection but not specifically addressed in the body of the rejection have inherited the deficiencies of their parent claim and have not resolved the deficiencies. Therefore, they are rejected based on the same rationale as applied to their parent claims above.
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 1-10 and 12 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception, is directed to that judicial exception (an abstract idea), as it has not been integrated into a practical application and the claim(s) further do/does not recite significantly more than the judicial exception. Examiner has evaluated the claim(s) under the framework provided in MPEP 2106 and has provided such analysis below.
To determine if a claim is directed to patent ineligible subject matter, the Court
has guided the Office to apply the Alice/Mayo test, which requires:
Step 1. Determining if the claim falls within a statutory category of a Process, Machine, Manufacture, or a Composition of Matter (see MPEP 2106.03);
Step 2A. Determining if the claim is directed to a patent ineligible judicial exception consisting of a law of nature, a natural phenomenon, or abstract idea (MPEP 2106.04);
Step 2A is a two-prong inquiry. MPEP 2106.04(II)(A).
Under the first prong, examiners evaluate whether a law of nature, natural phenomenon, or abstract idea is set forth or described in the claim. Abstract ideas include mathematical concepts, certain methods of organizing human activity, and mental processes. MPEP 2106.04(a)(2).
The second prong is an inquiry into whether the claim integrates a judicial exception into a practical application. MPEP 2106.04(d).
Step 2B. If the claim is directed to a judicial exception, determining if the claim recites limitations or elements that amount to significantly more than the judicial exception. (See MPEP 2106).
Step 1:
Claims 1-9 are directed to a device, and as such these claims fall within the statutory category of machine.
Claim 10 is directed to a method, as such these claims fall within the statutory category of process.
Claim 12 is directed to a non-transitory CRM, as such these claims fall within the statutory category of manufacture.
Step 2A, Prong 1:
The examiner submits that the foregoing claim limitations constitute abstract ideas, as the claims cover Mental Processes and/or Mathematical Concepts, given the broadest reasonable interpretation.
In order to apply Step 2A, a recitation of claims is copied below. The limitations of those claims which describe an abstract idea are bolded.
As per claim 1, the claim recites the limitations of:
a decision rule definition section that defines a decision rule concerning
whether the CAD model violates a design guideline; (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). Mental Processes are defined as concepts that can practically be performed in the human mind, or by a human using pen and paper as a physical aid. Examples of mental processes include observations, evaluations, judgments, and opinions. This limitation is directed towards performing a mental process on a generic computer. The core idea of defining a rule to check a design against a guideline is a mental process since humans can perform the same process, even if tediously, without a specific, innovative machine.)
a geometric shape recognition section that extracts non-conforming spots
that violate the design guideline for the CAD model based on geometric shapes according to the decision rule, wherein the geometric shape recognition section creates an executable rule of checks by combining (i) the decision rule and (ii) at least one procedure function selected from the geometric shape recognition function database, and executes the executable rule of checks on the CAD model to output the non-conforming spots; (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). This limitation is directed towards performing a mental process on a generic computer. For instance, a person is reasonably capable of evaluating a CAD model and determining whether or not the model violates design guidelines based on geometric shapes, with/without the aid of pen/paper. Additionally, per MPEP 2106.04(a)(2)(III)(A), “[e]xamples of claims that recite mental processes include: a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind”.) and
a feature value recognition section that extracts a first non-conforming
spot from among the non-conforming spots extracted by the geometric shape recognition section that violates the design guideline based on a feature value according to a prescribed feature value of the non-conforming spots extracted by the geometric shape recognition section. (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). This limitation is directed towards performing a mental process on a generic computer. For instance, a person is reasonably capable of evaluating a CAD model and determining whether or not the model violates a design guideline based on feature value(s). Additionally, per MPEP 2106.04(a)(2)(III)(A), “[e]xamples of claims that recite mental processes include: a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind”.)
wherein the processor evaluates whether the non-conforming spots output by the geometric shape recognition section include over-detection by determining an amount of noise using a precision-and-recall evaluation, and when over-detection is determined, invokes the feature value recognition section to reduce the noise and extract the first non-conforming spot (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). This limitation is directed towards performing a mental process on a generic computer. For instance, a person can reasonably evaluate (i.e. mental process) a model to determine if a section is over-detected via a precision-and-recall evaluation (i.e. mental process) and then extract/remove the first non-conforming section/spot. Additionally, per MPEP 2106.04(a)(2)(III)(A), “[e]xamples of claims that recite mental processes include: a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind”.)
converting each non-conforming spot into image data as projections in a plurality of directions (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mathematical Concepts). Per MPEP 2106.04(a)(2)(I)), “[t]he mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations [ ] [e]xamples of mathematical relationships recited in a claim include: a conversion between binary coded decimal and pure binary”.),
extracting an image feature value from the image data, and selecting the first non-conforming spot by reference to the image feature database storing image feature values of parts that violate the decision rule (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). This limitation is directed towards performing a mental process on a generic computer. For instance, a person can reasonably evaluate/extract a feature value from data and then compare that value to other feature values of parts that violate a decision rule and select the first non-conforming spot therefrom. Additionally, per MPEP 2106.04(a)(2)(III)(A), “[e]xamples of claims that recite mental processes include: a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind”.)
converting each non-conforming spot into STL data (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mathematical Concepts). Per MPEP 2106.04(a)(2)(I)), “[t]he mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations [ ] [e]xamples of mathematical relationships recited in a claim include: a conversion between binary coded decimal and pure binary”.)
calculating normal vectors of opposing surfaces from the STL data, determining a bending direction using an inner product of the normal vectors, excluding over-detected spots using the determined bending direction, and selecting the first non-conforming spot. (As drafted, and under BRI, these limitations amount to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III) and/or Mathematical Concepts MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. These limitations are directed towards performing a mental process on a generic computer. For instance, a person can reasonably calculate normal vectors of opposing surfaces, determine a bending direction using an inner product of the normal vectors, exclude over-detected spots using the determined bending direction, and then selecting the first non-conforming spot, with/without the aid of pen/paper.)
Step 2A, Prong 2:
As per claim 1, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present Mere Instructions To Apply An Exception and/or Field of Use and Technological Environment. In particular, the claim recites the additional limitations:
A design support device configured to evaluate flaws in a CAD model for a
physical object, the device comprising: at least one processor; a main storage storing the CAD model and program instructions; an auxiliary storage storing (i) a geometric shape recognition function database storing a plurality of procedure functions to recognize geometric shapes included in the CAD model and (ii) at least one of an image feature database and a geometric feature database; an input interface configured to receive the CAD model and a design guideline; and a display and a display control section configured to highlight a non-conforming spot on the display; (The additional element amounts to Mere Instructions to Apply an Exception (MPEP 2106.05(f)) and/or Field of Use and Technological Environment (MPEP 2106.05(h)). Per MPEP 2106.05(f), “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. This limitation is directed towards implementing an abstract idea (i.e. mental process) or other exception on a generic computer. Per MPEP 2106.05(h), “[a]nother consideration when determining whether a claim integrates the 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 generally linking the use of a judicial exception to a particular technological environment or field of use [ ] [e]xamples of limitations that the courts have described as merely indicating a field of use or technological environment in which to apply a judicial exception include: iv. Specifying that the abstract idea of monitoring audit log data relates to transactions or activities that are executed in a computer environment, because this requirement merely limits the claims to the computer field”. )
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considered as an ordered combination and as a whole.
Step 2B:
For step 2B of the analysis, the Examiner must consider whether each claim limitation individually or as an ordered combination amounts to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same.
The additional elements as described in Step 2A Prong 2 are not sufficient to amount to significantly more than the judicial exception because the additional limitations are considered directed towards mere instructions to apply an exception and/or field of use and technological environment. Thus, for example, claims that amount to nothing more than instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible. See MPEP 2106.05(d)/(f)/(h).
For the foregoing reasons, claim 1 is directed to an abstract idea without significantly more and is rejected as not patent eligible under 35 U.S.C. 101.
Step 2A, Prong 1 (Claim 10):
The examiner submits that the foregoing claim limitations constitute abstract ideas, as the claims cover Mental Processes and/or Mathematical Concepts, given the broadest reasonable interpretation.
In order to apply Step 2A, a recitation of claims is copied below. The limitations of those claims which describe an abstract idea are bolded.
As per independent claim 10, the claim recites the limitations of:
defining a decision rule concerning whether a CAD model for a physical object violates a design guideline; (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). Mental Processes are defined as concepts that can practically be performed in the human mind, or by a human using pen and paper as a physical aid. Examples of mental processes include observations, evaluations, judgments, and opinions. This limitation is directed towards performing a mental process on a generic computer. The core idea of defining a rule to check a design against a guideline is a mental process since humans can perform the same process, even if tediously, without a specific, innovative machine.)
creating an executable rule of checks by combining (i) the decision rule and (ii) at least one procedure function selected from a geometric shape recognition function database storing a plurality of procedure functions to recognize geometric shapes included in the CAD model; extracting non-conforming spots that violate the design guideline for the CAD model based on geometric shapes by executing the executable rule of checks according to the decision rule; (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). This limitation is directed towards performing a mental process on a generic computer. For instance, a person is reasonably capable of evaluating a CAD model and determining whether or not the model violates a design guideline based on geometric shapes, with/without the aid of pen/paper. Additionally, per MPEP 2106.04(a)(2)(III)(A), “[e]xamples of claims that recite mental processes include: a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind”.)
evaluating whether the extracted non-conforming spots include over-detection by determining an amount of noise using a precision-and-recall evaluation; and extracting a first non-conforming spot from among the extracted non-conforming spots that violates the design guideline based on a feature value according to a prescribed feature value of the extracted non-conforming spots. (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). This limitation is directed towards performing a mental process on a generic computer. For instance, a person can reasonably evaluate (i.e. mental process) a model to determine if a section is over-detected via a precision-and-recall evaluation (i.e. mental process) and then extract/remove the first non-conforming section/spot. Additionally, per MPEP 2106.04(a)(2)(III)(A), “[e]xamples of claims that recite mental processes include: a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind”.)
converting each non-conforming spot into image data as projections in a plurality of directions (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mathematical Concepts). Per MPEP 2106.04(a)(2)(I)), “[t]he mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations [ ] [e]xamples of mathematical relationships recited in a claim include: a conversion between binary coded decimal and pure binary”.),
extracting an image feature value from the image data, and selecting the first non-conforming spot by reference to the image feature database storing image feature values of parts that violate the decision rule (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). This limitation is directed towards performing a mental process on a generic computer. For instance, a person can reasonably evaluate/extract a feature value from data and then compare that value to other feature values of parts that violate a decision rule and select the first non-conforming spot therefrom. Additionally, per MPEP 2106.04(a)(2)(III)(A), “[e]xamples of claims that recite mental processes include: a claim to collecting and comparing known information (claim 1), which are steps that can be practically performed in the human mind”.)
converting each non-conforming spot into STL data (As drafted, and under its broadest reasonable interpretation, this limitation amounts to an Abstract Idea (Mathematical Concepts). Per MPEP 2106.04(a)(2)(I)), “[t]he mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations [ ] [e]xamples of mathematical relationships recited in a claim include: a conversion between binary coded decimal and pure binary”.)
calculating normal vectors of opposing surfaces from the STL data, determining a bending direction using an inner product of the normal vectors, excluding over-detected spots using the determined bending direction, and selecting the first non-conforming spot. (As drafted, and under BRI, these limitations amount to an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III) and/or Mathematical Concepts MPEP 2106.04(a)(2)(I)). The mathematical concepts grouping is defined as mathematical relationships, mathematical formulas or equations, and mathematical calculations. A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping. These limitations are directed towards performing a mental process on a generic computer. For instance, a person can reasonably calculate normal vectors of opposing surfaces, determine a bending direction using an inner product of the normal vectors, exclude over-detected spots using the determined bending direction, and then selecting the first non-conforming spot, with/without the aid of pen/paper.)
Step 2A, Prong 2 (Claim 10):
As per claim 10, this judicial exception is not integrated into a practical application because the additional claim limitations outside the abstract idea only present Mere Instructions To Apply An Exception and/or Insignificant Extra-Solution Activity. In particular, the claim recites the additional limitations:
A design support method that is performed by a design support device (The additional element amounts to Mere Instructions to Apply an Exception per MPEP 2106.05(f). Per MPEP 2106.05(f), “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. This limitation is directed towards implementing an abstract idea (i.e. mental process) or other exception on a generic computer (i.e. design support device).
highlighting the first non-conforming spot on a display (The additional element amounts to Insignificant Extra-Solution Activity per MPEP 2106.05(g). The term "extra-solution activity" can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. Adding a final step of highlighting the first non-conforming spot on a display does not meaningfully limit the claim and is interpreted as post-solution activity.)
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea when considered as an ordered combination and as a whole.
Step 2B (Claim 10):
For step 2B of the analysis, the Examiner must consider whether each claim limitation individually or as an ordered combination amounts to significantly more than the abstract idea. This analysis includes determining whether an inventive concept is furnished by an element or a combination of elements that are beyond the judicial exception. For limitations that were categorized as “apply it” or generally linking the use of the abstract idea to a particular technological environment or field of use, the analysis is the same.
The additional elements as described in Step 2A Prong 2 are not sufficient to amount to significantly more than the judicial exception because the additional limitations are considered directed towards mere instructions to implement an abstract idea or other exception on a computer and/or insignificant extra-solution activity. Per MPEP 2106.05(f), “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.” Per MPEP 2106.05(g), “[a]s explained by the Supreme Court, the addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional.”
Per MPEP 2106.05(d), “when determining whether a claim recites significantly more than a judicial exception is whether the additional element(s) are well-understood, routine, conventional activities previously known to the industry.” The limitation of highlighting non-conforming spots is a WURC activity previously known to the industry, as evident by Hariya [Pg.297 Fig.2], referenced art in Claim Rejections - 35 U.S.C. 103 section below. See Fig.2 below.
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For the foregoing reasons, claim 10 is directed to an abstract idea without significantly more and is rejected as not patent eligible under 35 U.S.C. 101.
Independent claim 12 recites substantially the same subject matter as claim 10 and is rejected under similar rationale. Claim 12 further recites A non-transitory computer-readable medium storing instructions that, when executed by a computer, causes the computer to perform a method of. The additional limitation is directed towards Mere Instructions to Apply an Exception per MPEP 2106.05(f). Specifically, this limitation is directed towards mere instructions to implement an abstract idea (i.e. mental process) or other exception on a computer. Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 2 further recites, wherein if the non-conforming spots extracted by the geometric shape recognition section are over-detected, the first non-conforming spot that violates the design guideline is extracted from among the non-conforming spots based on the feature value. The additional limitations are further directed towards an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). This limitation is directed towards performing a mental process on a generic computer. For instance, a person can reasonably determine (i.e. evaluate, judge) if the non-conforming spots are over-detected then identify/extract the first non-conforming spot based on a feature value, with/without the aid of pen/paper. Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 3, the design support device according to claim 2, further recites, wherein even if the first non-conforming spot that violates the design guideline is extracted based on the feature value according to a first feature value as the prescribed feature value but the non-conforming spots are still over-detected, a second non-conforming spot that violates the design guideline is extracted according to a second feature value different from the first feature value, based on the second feature value. The additional limitations are further directed towards an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). This limitation is directed towards performing a mental process on a generic computer, since a person can reasonably perform the limitation with/without the aid of pen/paper. See claim 2 for similar rationale. Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 4 further recites, wherein the prescribed feature value is an image feature value of the non-conforming spot, and the feature value recognition section refers to an image feature database storing an image feature value of a part that violates the decision rule and extracts the first non-conforming spot that violates the design guideline according to the image feature value. The additional limitations elaborate on the prescribed feature value and its use for extracting the first non-conforming spot, thus further amounts to Mental Processes performed on a computer per MPEP 2106.04(a)(2)(III). Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 5, the design support device according to Claim 4, further recites wherein the image feature database stores, as the image feature value of the part that violates the decision rule, an image feature value of each of a plurality of images of the part that are taken at different view angles. The additional limitations are directed towards Insignificant Extra-solution Activity per MPEP 2106.05(g). The term "extra-solution activity" can be understood as activities incidental to the primary process or product that are merely a nominal or tangential addition to the claim. Extra-solution activity includes both pre-solution and post-solution activity. An example of pre-solution activity is a step of gathering data for use in a claimed process. See MPEP 2106.05(d) for Well-Understood, Routine, Conventional Activity. MPEP 2106.05(d)(II)(iv) states, “Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93;”. Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 6, the design support device according to Claim 4, further recites wherein the feature value recognition section refers to the image feature database as a database storing teacher data for machine learning and extracts the first non-conforming spot that violates the design guideline according to a result of the machine learning. The additional limitations further elaborate the feature value recognition section from which this claim depends, and thus is further directed towards Mental Processes performed on a computer per MPEP 2106.04(a)(2)(III). Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 7 further recites, wherein the prescribed feature value is a geometric feature value of the non-conforming spots, and the feature value recognition section extracts the first non-conforming spot that violates the design guideline according to the geometric feature value. The additional limitations further elaborate on the prescribed feature value and the feature value recognition section which were deemed mental processes in the claim from which the limitations depend. Thus, the additional limitations are further directed towards an Abstract Idea (Mental Processes MPEP 2106.04(a)(2)(III)). Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 8, the design support device according to Claim 7, further recites wherein the feature value recognition section converts the non-conforming spots extracted by the geometric shape recognition section, into prescribed data from which a geometric feature value can be extracted, and extracts the first non-conforming spot that violates the design guideline according to the geometric feature value on the prescribed data. The additional limitations are directed towards Mere Instructions to Apply an Exception per MPEP 2106.05(f). Specifically, this limitation is directed towards mere instructions to implement an abstract idea or other exception on a computer. Also, converting data into “prescribed data” is considered Insignificant Extra-solution Activity (mere data gathering and outputting) per MPEP 2106.05(g). See MPEP 2106.05(d)(II)(ii)/(iv). Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim 9, The design support device according to Claim 8, further recites wherein the prescribed data is STL (Stereolithography) data, and the feature value recognition section extracts the first non-conforming spot that violates the design guideline according to the geometric feature value on the STL data. The additional limitations are directed towards Insignificant Extra-solution Activity and/or Field of Use per MPEP 2106.05(g)/(h) (reference MPEP 2106.05(d)). For instance, a data gathering step that is limited to a particular type of data (i.e. STL data) is considered to be both insignificant extra-solution activity and a field of use limitation. The limitation is also directed towards Mere Instructions to Apply an Exception (i.e. mere instructions to implement an abstract idea or other exception on a computer) per MPEP 2106.05(f). Therefore, the claim is not patent eligible under 35 U.S.C. 101.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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 set forth in Graham V. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) 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, 2, 4, 5, 7-10, and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Itabayashi et al. US Pub No. 20130321415 A1 (hereinafter referred to as “Itabayashi”) in view of Hariya, Masayuki, et al. "Technique for checking design rules for three-dimensional CAD data." 2010 3rd International Conference on Computer Science and Information Technology. Vol. 1. IEEE, 2010. (hereinafter referred to as “Hariya”), and in view of Lu, T. "Towards a fully automated 3D printability checker, in an international conference on Industrial Technology (ICIT)." (2016): 922-927 (hereinafter referred to as “Lu”).
Regarding claim 1, Itabayashi discloses, A design support device configured to evaluate flaws in a CAD model for a physical object (“the present invention is to reduce errors in analytical model creation [ ] a device for creating a numerical analytical model from CAD data” [P.0009-10]), the device comprising: at least one processor; a main storage storing the CAD model and program instructions; an auxiliary storage storing (i) a geometric shape recognition function database storing a plurality of procedure functions to recognize geometric shapes included in the CAD model and (ii) at least one of an image feature database and a geometric feature database; an input interface configured to receive the CAD model and a design guideline; and a display and a display control section configured to highlight a non-conforming spot on the display (“ FIG. 1 (see below) is a schematic diagram of a design support system including an analytical model information delivery device” [P.0034]);
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a decision rule definition section that defines a decision rule concerning whether a CAD model violates a design guideline (“a shape creation rule (i.e. decision rule) prestored (i.e. defined) in an analytical modeling means database” [P.0014]); a feature value recognition section that extracts a first non-conforming spot from among the non-conforming spots extracted by the geometric shape recognition section that violates the design guideline based on a feature value according to a prescribed feature value of the non-conforming spots extracted by the geometric shape recognition section. (“by comparing the information stored in the CAD feature shape database 111 against the rules given by the analytical modeling means database 112, extracts features of the CAD data” [P.0074]) invokes the feature value recognition section to reduce the noise and extract the first non-conforming spot (“by comparing the information stored in the CAD feature shape database 111 against the rules given by the analytical modeling means database 112, extracts features of the CAD data” [P.0074]. Note: See Examiner’s claim interpretation in section above.), wherein extracting the first non-conforming spot by the feature value recognition section comprises at least one of: , calculating normal vectors of opposing surfaces (“In determining the distances d between planes 401a to 401k of part 1 and planes 406a to 406f of part 2, the distance [ ] is determined along with normal vectors between part 1 and part 2” [P.0059]), determining a bending direction using an inner product of the normal vectors (“the present invention can be applied to the processing of all types of features including not only holes and gaps but also fillets and chamfers (i.e. bending directions)” [P.0089]), excluding spots using the determined bending direction (“With reference to FIG. 6 (see below), an analytical modeling means will be described. FIG. 6 shows example contents of the analytical modeling means database 112. The analytical modeling means database 112 stores the determination conditions based on which interactive queries about how to model feature shapes in creating analytical models can be sent to an analyzer. The table stored in the analytical modeling means database 112 includes, arranged along the row direction, a shape feature type / feature name column 502, a parameter column 503, an analysis object column 504, a determination condition column 505, and a query contents column 506.) [P.0066]. In Fig. 6 below, QUERY CONTENTS column labeled “IS FILLET (or CHAMFER) TO BE DELETED” with PARAMETER/DETERMINATION columns are interpreted as excluding spots using the bending direction, i.e. fillet or chamfer.), and selecting the first non-conforming spot (“by comparing the information stored in the CAD feature shape database 111 against the rules given by the analytical modeling means database 112, extracts features of the CAD data” [P.0074]).
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Itabayashi fails to specifically disclose a geometric shape recognition section that
extracts non-conforming spots that violate the design guideline for the CAD model based on geometric shapes according to the decision rule; wherein the geometric shape recognition section creates an executable rule of checks by combining (i) the decision rule and (ii) at least one procedure function selected from the geometric shape recognition function database, and executes the executable rule of checks on the CAD model to output the non-conforming spots, wherein the processor evaluates whether the non-conforming spots output by the geometric shape recognition section include over-detection by determining an amount of noise using a precision-and-recall evaluation, and when over-detection is determined, and converting each non-conforming spot into STL data.
However, Hariya discloses a geometric shape recognition section that
extracts non-conforming spots that violate the design guideline for the CAD model based on geometric shapes according to the decision rule (“The feature
recognition part extracts feature shapes from a CAD model according to inputted thickness. The rule check part compares a feature shape's parameters with design rules
stored in the rule database, and it extracts the violation portion (i.e. non-conforming spots) and violation rules. The visualization part displays the results of the rule check in the 3D CAD” Hariya [Pg.297 B. Configuration]), wherein the geometric shape recognition section creates an executable rule of checks by combining (i) the decision rule and (ii) at least one procedure function selected from the geometric shape recognition function database (“The feature shapes that should be recognized for the design rule check and the parameter are shown in Table I (see below) [ ] The thickness (i.e. at least one procedure function) is used for recognizing the feature shape and for the design rule check” Hariya [Pg.297 C. Feature recognition technique]. The thickness is interpreted as at least one procedure function due to Applicant’s disclosure “a plurality of procedure functions to recognize a geometric shape included in the CAD model as the check object (hereinafter called common functions)” Spec. [P.0022]. The at least one procedure function is interpreted to be selected from a database because “parameters are also registered in the database.” Hariya [Pg.298 D. Design rule database]),
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and executes the executable rule of checks on the CAD model to output the non-conforming spots (“The feature recognition part extracts feature shapes from a CAD model according to inputted thickness. The rule check part compares a feature shape's parameters with design rules stored in the rule database, and it extracts the violation portion (i.e. non-conforming spots) and violation rules. The visualization part displays the results of the rule check in the 3D CAD” Hariya [Pg.297 B. Configuration])
Itabayashi and Hariya are analogous art as they both relate to processing CAD data/models and extracting or recognizing features from CAD models. They use rules or guidelines (shape creation rules or decision rules) and databases to compare or validate extracted features. Both involve some form of interactive or automated correction / identification process and support computer-implemented methods and programs for their respective processes. Itabayashi discloses “A shape search unit searches the components making up the CAD data and extracts features, and matches the extracted features with shape creation rules pre-registered in an analytical modeling means database” [Abstract], and Hariya discloses “A technique was developed for checking whether three-dimensional CAD shape satisfies design rules [ ] Our technique automatically recognizes feature shapes such as a rib and boss from a CAD model shape, and it checks the shape and arrangement” [Abstract]. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Itabayashi’s design support device to include the extraction and output of non-conforming CAD model spots based on guidelines/rules, as Hariya discloses, so “that the number of defects and problems is decreased in products (i.e. product design)” Hariya [Pg.1 Col.2 P.1].
However, Hariya also fails to specifically disclose wherein the processor evaluates whether the non-conforming spots output by the geometric shape recognition section include over-detection by determining an amount of noise using a precision-and-recall evaluation, and when over-detection is determined invokes the feature value recognition section to reduce the noise and extract the first non-conforming spot and converting each non-conforming spot into STL data.
Lu discloses wherein the processor evaluates whether the non-conforming spots output by the geometric shape recognition section include over-detection by determining an amount of noise using a precision-and-recall evaluation (“Fig. 4 illustrates the precision-recall curve of the test result. Recall that the values in this graph are calculated by the rate of true positive (Tp), false positive (Fp) and false negative (Fn). True positive means the prediction positive value is true positive indeed. False positive (i.e. over-detection) means the predicted positive value should be negative. False negative means the predicted negative value should be indeed positive. The precision represents the rate of true positive under all positive predictions and recall indicates the rate of “completeness” of the correct labelling.” Lu [Pg.925-926 C. Result]), and when over-detection is determined (See Lu [Pg.925-926 C. Result] for precision and recall evaluation.) (See Itabayashi [P.0074]), and converting into STL data (“3D graphics and CAD techniques are reused to provide user interface to transform a 3D object to printing format, e.g. Stereolithography (STL).” Lu [Pg.922 I. Introduction]).
Lu is analogous art as it relates to CAD geometry modeling/design and associated constraint rules. Lu discloses “a generic framework to automatically check the 3D printability of a given 3D model [ ] The framework uses formal method in system design for 3D Object processing [ ] The generic design of the framework shown in Section III allows combination of formal techniques, classical geometry modelling and machine learning methods” [Pg.926 VIII. Conclusion]. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Itabayashi’s design support device to include determining over-detection by using a precision-and-recall evaluation and the use of STL data, as Lu discloses, since “precision represents the rate of true positive under all positive predictions and recall indicates the rate of “completeness” of the correct labelling (i.e. recognizing over-detection)” Lu [Pg.925 Col.2 P.6], and since STL is a simple file format used universally and is compatible with most CAD software, ensuring efficient communication between design programs, as well as “to provide user interface to transform a 3D object to printing format” Lu [Pg.922 I. Introduction].
Regarding claim 2, Itabayashi further discloses, ,
the first non-conforming spot that violates the design guideline is extracted from among the non-conforming spots based on the feature value (“by comparing the information stored in the CAD feature shape database 111 against the rules given by the analytical modeling means database 112, extracts features of the CAD data” [P.0074]).
Itabayashi fails to specifically disclose wherein if the non-conforming spots extracted by the geometric shape recognition section are over-detected.
However, Lu discloses recognizing over-detection via a precision-and-recall evaluation (See Lu [Pg.925-926 C. Result]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to extract the first non-conforming spot that violates a design guideline, as Itabayashi discloses, if the extracted spot is over-detected, as Lu discloses, in order “to reduce errors in analytical model creation” Itabayashi [P.0009].
Regarding claim 4, Itabayashi further discloses, wherein the prescribed feature value is an image feature value of the non-conforming spot, (“FIG. 5 shows diagrams describing contents of the CAD feature shape database” Itabayashi [P.0021])
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and the feature value recognition section refers to an image feature database storing an image feature value of a part (“stores the shape feature in a CAD feature shape database (i.e. image feature database)” Itabayashi [P.0014]) that violates the decision rule and extracts the first non-conforming spot that violates the design guideline according to the image feature value. (“a query unit which compares a result of searching made by the shape search unit against a shape creation rule prestored in an analytical modeling means database and instructs an input/output device to present the result” Itabayashi [P.0014])
Regarding claim 5, Itabayashi further discloses, wherein the image feature database stores, as an image feature value of the part that violates the decision rule, an image feature value of each of a plurality of images of the part that are taken at different view angles. (“When the distance between plane 401e and plane 406a is within a threshold set as a determination condition or when the angle formed between the two normal vectors 409 and 410 is nearly 180 degrees, the portion is determined as a gap [ ] When making a query for "gap," the "gap" information (i.e. image feature value) is registered and stored in the CAD feature shape database (i.e. image feature database) 111 (step S310). At the same time, the portion to be highlighted on the display is set (step S311).” Itabayashi [P.0059-60]. See Fig 5 below for plurality of images of the one part.)
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Regarding claim 7, Itabayashi fails to specifically disclose wherein the prescribed feature value is a geometric feature value of the non-conforming spots, and the feature value recognition section extracts the first non-conforming spot that violates the design guideline according to the geometric feature value.
However, Hariya discloses wherein the prescribed feature value is a geometric feature value of the non-conforming spots, and the feature value recognition section extracts the first non-conforming spot that violates the design guideline according to the geometric feature value (“The feature recognition part extracts feature shapes from a CAD model according to inputted thickness. The rule check part compares a feature shape's parameters with design rules stored m the rule database, and it extracts the violation portion and violation rules.” Hariya [Pg.297 B. Configuration])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Itabayashi’s design support device to include feature value recognition, as Hariya discloses, so “that the number of defects and problems is decreased in products (i.e. product design)” Hariya [Pg.1 Col.2 P.1].
Regarding claim 8, Itabayashi further discloses, wherein the feature value recognition section converts a non-conforming spot extracted by the geometric shape recognition section, into prescribed data from which a geometric feature value can be extracted, and extracts the first non-conforming spot that violates the design guideline according to the geometric feature value on the prescribed data. (“The portion determined as a gap (i.e. geometric feature) is highlighted (see step S318). Whether or not to close the gap is determined by the analyzer (i.e. extracting a non-conforming spot) after the analytical model is created by conversion.” Itabayashi [P.0078]. Examiner interprets the analytical model to include prescribed data because “the model conversion unit 107 included in the computing device 150 converts the three-dimensional CAD model into an analytical CAD model” Itabayashi [P.0045] and “an analytical model information delivery device is provided in a device for creating a numerical analytical model from CAD data” Itabayashi [P.0010])
Regarding claim 9, Itabayashi further discloses, , and the feature value recognition section extracts the first non-conforming spot that violates the design guideline according to the geometric feature value (see claim 1 reference, Itabayashi [P.0074]) .
Itabayashi fails to specifically disclose wherein the prescribed data is STL (Stereolithography) data.
However, Lu further discloses wherein the prescribed data is STL (Stereolithography) data (“3D graphics and CAD techniques are reused to provide user interface to transform a 3D object to printing format, e.g. Stereolithography (STL).” Lu [Pg.922 I. Introduction])
It would have been obvious to one of ordinary skill in the art before the
Applicant' s effective filling date of the claimed invention to have modified Itabayashi to incorporate STL data, as disclosed by Lu, since STL is a simple file format used universally and is compatible with most CAD software, ensuring efficient communication between design programs, as well as “to provide user interface to transform a 3D object to printing format” Lu [Pg.922 I. Introduction].
Regarding independent claim 10, Itabayashi discloses, A design support method that is performed by a design support device, wherein the design support method includes the steps of: (“a device for creating a numerical analytical model from CAD data” [P.0010]) defining a decision rule concerning whether a CAD model for a physical object violates a design guideline; (“a shape creation rule (i.e. decision rule) prestored (i.e. defined) in an analytical modeling means database” [P.0014]) ; and extracting a first non-conforming spot from among the extracted non-conforming spots that violates the design guideline based on a feature value according to a prescribed feature value of the extracted non-conforming spots (“by comparing the information stored in the CAD feature shape database 111 against the rules given by the analytical modeling means database 112, extracts features of the CAD data” [P.0074]), calculating normal vectors of opposing surfaces (“In determining the distances d between planes 401a to 401k of part 1 and planes 406a to 406f of part 2, the distance [ ] is determined along with normal vectors between part 1 and part 2” [P.0059]), determining a bending direction using an inner product of the normal vectors (“the present invention can be applied to the processing of all types of features including not only holes and gaps but also fillets and chamfers (i.e. bending directions)” [P.0089]), excluding spots using the determined bending direction (“With reference to FIG. 6 (see below), an analytical modeling means will be described. FIG. 6 shows example contents of the analytical modeling means database 112. The analytical modeling means database 112 stores the determination conditions based on which interactive queries about how to model feature shapes in creating analytical models can be sent to an analyzer. The table stored in the analytical modeling means database 112 includes, arranged along the row direction, a shape feature type / feature name column 502, a parameter column 503, an analysis object column 504, a determination condition column 505, and a query contents column 506.) [P.0066]. In Fig. 6 below, QUERY CONTENTS column labeled “IS FILLET (or CHAMFER) TO BE DELETED” with PARAMETER/DETERMINATION columns are interpreted as excluding spots using the bending direction, i.e. fillet or chamfer.), and selecting the first non-conforming spot (“by comparing the information stored in the CAD feature shape database 111 against the rules given by the analytical modeling means database 112, extracts features of the CAD data” [P.0074])
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Itabayashi fails to specifically disclose creating an executable rule of checks by combining (i) the decision rule and (ii) at least one procedure function selected from a geometric shape recognition function database storing a plurality of procedure functions to recognize geometric shapes included in the CAD model; extracting non-conforming spots that violate the design guideline for the CAD model based on geometric shapes by executing the executable rule of checks according to the decision rule; evaluating whether the extracted non-conforming spots include over-detection by determining an amount of noise using a precision-and-recall evaluation; (i) converting each non-conforming spot into image data as projections in a plurality of directions, extracting an image feature value from the image data, and selecting the first non-conforming spot by reference to an image feature database storing image feature values of parts that violate the decision rule; or (ii) converting each non-conforming spot into STL data, and highlighting the first non-conforming spot on a display.
However, Hariya discloses creating an executable rule of checks by combining (i) the decision rule and (ii) at least one procedure function selected from a geometric shape recognition function database storing a plurality of procedure functions to recognize geometric shapes included in the CAD model (“The feature shapes that should be recognized for the design rule check and the parameter are shown in Table I (see below) [ ] The thickness (i.e. at least one procedure function) is used for recognizing the feature shape and for the design rule check” Hariya [Pg.297 C. Feature recognition technique]. The thickness is interpreted as at least one procedure function due to Applicant’s disclosure “a plurality of procedure functions to recognize a geometric shape included in the CAD model as the check object (hereinafter called common functions)” Spec. [P.0022]. The at least one procedure function is interpreted to be selected from a database because “parameters are also registered in the database.” Hariya [Pg.298 D. Design rule database]),
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extracting non-conforming spots that violate the design guideline for the CAD model based on geometric shapes by executing the executable rule of checks according to the decision rule (“The feature recognition part extracts feature shapes from a CAD model according to inputted thickness. The rule check part compares a feature shape's parameters with design rules stored in the rule database, and it extracts the violation portion (i.e. non-conforming spots) and violation rules. The visualization part displays the results of the rule check in the 3D CAD” Hariya [Pg.297 B. Configuration]), and highlighting the first non-conforming spot on a display (“The display when the violation occurs is shown in figure 7. The violation portions are displayed according to list format [ ] When the item of the list is selected, the system highlights violation part (i.e. non-conforming spot). So, the designer can specify the violation part easily.” Hariya [Pg.299 Col.1 P.6]).
Itabayashi and Hariya are analogous art as they both relate to processing CAD data/models and extracting or recognizing features from CAD models. They use rules or guidelines (shape creation rules or decision rules) and databases to compare or validate extracted features. Both involve some form of interactive or automated correction / identification process and support computer-implemented methods and programs for their respective processes. Itabayashi discloses “A shape search unit searches the components making up the CAD data and extracts features, and matches the extracted features with shape creation rules pre-registered in an analytical modeling means database” [Abstract], and Hariya discloses “A technique was developed for checking whether three-dimensional CAD shape satisfies design rules [ ] Our technique automatically recognizes feature shapes such as a rib and boss from a CAD model shape, and it checks the shape and arrangement” [Abstract]. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Itabayashi’s design support device to include the extraction and output of non-conforming CAD model spots based on guidelines/rules, as Hariya discloses, so “that the number of defects and problems is decreased in products (i.e. product design)” Hariya [Pg.1 Col.2 P.1].
However, Hariya also fails to specifically disclose evaluating whether the extracted non-conforming spots include over-detection by determining an amount of noise using a precision-and-recall evaluation, and converting each non-conforming spot into STL data.
Lu discloses evaluating whether the extracted non-conforming spots include over-detection by determining an amount of noise using a precision-and-recall evaluation (“Fig. 4 illustrates the precision-recall curve of the test result. Recall that the values in this graph are calculated by the rate of true positive (Tp), false positive (Fp) and false negative (Fn). True positive means the prediction positive value is true positive indeed. False positive (i.e. over-detection) means the predicted positive value should be negative. False negative means the predicted negative value should be indeed positive. The precision represents the rate of true positive under all positive predictions and recall indicates the rate of “completeness” of the correct labelling.” Lu [Pg.925-926 C. Result]); converting into STL data (“3D graphics and CAD techniques are reused to provide user interface to transform a 3D object to printing format, e.g. Stereolithography (STL).” Lu [Pg.922 I. Introduction]).
Lu is analogous art as it relates to CAD geometry modeling/design and associated constraint rules. Lu discloses “a generic framework to automatically check the 3D printability of a given 3D model [ ] The framework uses formal method in system design for 3D Object processing [ ] The generic design of the framework shown in Section III allows combination of formal techniques, classical geometry modelling and machine learning methods” [Pg.926 VIII. Conclusion]. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Itabayashi’s design support device to include determining over-detection by using a precision-and-recall evaluation and the use of STL data, as Lu discloses, since “precision represents the rate of true positive under all positive predictions and recall indicates the rate of “completeness” of the correct labelling (i.e. recognizing over-detection)” Lu [Pg.925 Col.2 P.6], and since STL is a simple file format used universally and is compatible with most CAD software, ensuring efficient communication between design programs, as well as “to provide user interface to transform a 3D object to printing format” Lu [Pg.922 I. Introduction].
Regarding independent claim 12, Itabayashi discloses, A non-transitory computer-readable medium storing instructions that, when executed by a computer, causes the computer to perform a method of: (“still another characteristic of the present invention made to achieve the above objects is that an analytical model information delivery program is installed in a device for creating a numerical analytical model from CAD data and that the program causes a computer to function as...” Itabayashi [P.0014])
The remaining limitations recite substantially the same subject matter as claim 10 and are rejected under similar rationale. Itabayashi teaches the additional limitations of Claim 12, and maintains the same rationale for combination with Hariya and Lu as Claim 10.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Itabayashi et al. US Pub No. 20130321415 A1 (hereinafter referred to as “Itabayashi”) in view of Hariya, Masayuki, et al. "Technique for checking design rules for three-dimensional CAD data." 2010 3rd International Conference on Computer Science and Information Technology. Vol. 1. IEEE, 2010. (hereinafter referred to as “Hariya”), and in view of Lu, T. "Towards a fully automated 3D printability checker, in an international conference on Industrial Technology (ICIT)." (2016): 922-927 (hereinafter referred to as “Lu”), and in further view of Harigai et al. JP 2010277460 A (hereinafter referred to as “Harigai”).
Regarding claim 3, Itabayashi fails to specifically disclose wherein even if the first non-conforming spot that violates the design guideline is extracted based on the feature value according to a first feature value as the prescribed feature value but the non-conforming spots are still over-detected, a second non-conforming spot that violates the design guideline is extracted according to a second feature value different from the first feature value, based on the second feature value.
However, Harigai discloses wherein even if the first non-conforming spot that violates the design guideline is extracted based on the feature value according to a first feature value as the prescribed feature value but the non-conforming spots are still over-detected, a second non-conforming spot that violates the design guideline is extracted according to a second feature value different from the first feature value, based on the second feature value. (“Here, three design rules (i.e. guideline) are registered for the boss 22 of the feature type. These design rules are contents for determining whether a predetermined condition is satisfied or not satisfied (i.e. non-conforming) based on a dimensional parameter (i.e. first feature value) and an arrangement parameter (i.e. second feature value) of the shape of the created feature or a shape model.” Harigai [Pg.4 P.8])
Harigai is analogous art as it relates to CAD design support, focusing on rule-based checking and guidance for CAD models. Harigai discloses “a CAD shape creation support device capable of making an appropriate shape change to an unsatisfactory part of a design rule” [Abstract]. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to Itabayashi’s design support device to include multiple feature values, as Harigai discloses, for “sufficiently preventing design rework and improving design work efficiency” Harigai [Abstract].
Claim 6 is rejected under 35 U.S.C. 103 as being unpatentable over Itabayashi et al. US Pub No. 20130321415 A1 (hereinafter referred to as “Itabayashi”) in view of Hariya, Masayuki, et al. "Technique for checking design rules for three-dimensional CAD data." 2010 3rd International Conference on Computer Science and Information Technology. Vol. 1. IEEE, 2010. (hereinafter referred to as “Hariya”), and in view of Lu, T. "Towards a fully automated 3D printability checker, in an international conference on Industrial Technology (ICIT)." (2016): 922-927 (hereinafter referred to as “Lu”), in further view of TSUYOSHI et al. JP Pub. No. 7017462 B2 (hereinafter referred to as “Tsuyoshi”).
Regarding claim 6, Itabayashi further discloses, wherein the feature value recognition section (see claim 1 reference, Itabayashi [P.0074])
The Itabayashi fails to specifically disclose, refers to the image feature database as a database storing teacher data for machine learning and extracts the first non-conforming spot that violates the design guideline according to a result of the machine learning.
However, Tsuyoshi discloses, refers to the image feature database as a database storing (“The storage unit 32 contains a captured image (i.e. teacher data) database (DB) 32a that stores captured images of each component [ ] and a three-dimensional CAD that stores a three-dimensional CAD image of each component that is an object to be recognized. An image database (DB) 32b is provided” Tsuyoshi [Pg.3 P.4]) teacher data for machine learning and extracts the first non-conforming spot that violates the design guideline according to a result of the machine learning. (“an image recognition model, which is a machine learning model for performing image recognition [ ] This image recognition model [ ] is a model in which the captured image and the training image, which are teacher data, are input, and the shape information of the component is also output.” Tsuyoshi [Pg.5 P.8] , “a training image generated by the image generator 31b. It includes a learning device 31d that performs machine learning, and an image recognizer 31e that performs image recognition using a machine learning model obtained as a result of learning by the learning device 31d.” Tsuyoshi [Pg.8 P.1])
Tsuyoshi is analogous art as it relates to the same field of endeavor, specifically CAD design support devices. Tsuyoshi discloses “a learning image generation device and a learning image generation method for generating a learning image from CAD data, and an image recognition device and an image recognition method for performing image recognition using the learning image” [Pg.2 P.1]. It would have been obvious to one of ordinary skill in the art before the Applicant' s effective filling date of the claimed invention to have modified Itabayashi to include image recognition machine learning capabilities, as taught by Tsuyoshi, “in order to achieve high [image] recognition accuracy” Tsuyoshi [Pg.2 P.2].
Conclusion
The prior art made of record, listed on form PTO-892, and not relied upon is
considered pertinent to applicant's disclosure:
Hariya, Masayuki, et al. "Automatic hexahedral mesh generation with feature line extraction." Proceedings of the 15th International Meshing Roundtable. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. “An improved method using feature line extraction is described for automatically generating hexahedral meshes for complex geometric models that automate the normally interactive operations (such as model editing)” [Abstract]
Z. Sukimin and H. Haron, "Extraction and Recognition Algorithm in 3D Object Features," 2009 Third Asia International Conference on Modelling & Simulation, Bundang, Indonesia, 2009, pp. 57-60, “The procedure of automated recognition of extracting 3D object features is to match the geometric entities with the database of the design code. Different CAD packages use different types of database structure to store the information of the part in CAD file. Therefore, features in the feature database should be pre-defined.” [Sec.III Methodology]
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/ANTHONY CHAVEZ/ Examiner, Art Unit 2187
/RENEE D CHAVEZ/ Supervisory Patent Examiner, Art Unit 2186
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