DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. The amendment filed on 03/24/2026 has been received and fully considered.
3. Claims 1-10 are presented for examination.
Response to Arguments
4. Applicant's arguments filed 03/24/2026 have been fully considered but they are not persuasive. Regarding applicant’s assertions that: “the features recited in amended Claim 1 provide the very type of technological improvement to automated and/or computer-assisted design verification that MPEP 2106.04(a)(1) stated as an "improvement to any other technology or technical field" which cause the claims of this application to not be directed to an abstract idea” and “n the instant application, the claims solve the problem of verification of manufacturing system design based only on CAD information and control programs by using a design information model that integrates different classes of design information based on their relationships to allow validation to be performed using more diverse design information that just CAD information and control programs. Thus, the claims' specific use of this design information model - as in Example 41 - renders the claims patent eligible under 35 U.S.C. 101.”, the examiner respectfully disagrees and notes that the claims, as currently amended, are clearly directed to abstract idea and do not anything that goes beyond the judicial exception nor provide any integration of the recited abstract idea into a practical application. The claims further do not, in any way, provide any improvement to a technological field, as asserted by the Applicant. In fact, there absolutely no way to improve the functionality of the general processor by the steps set forth in the claims. Even assuming that that claim recites some sort of improvement, said improvement would only apply to Applicants’ method and not the computer in general, i.e. when other computer applications are executed, they do not benefit from the same improvement that Applicants intended to have produced. Furthermore, with the reference to example 41, the claims at issue is completely different than that of example 41; the fact pattern simply do not match. As such the claims are abstract. As per applicant’s assertions that: “Suzuki does not disclose defining a class to classify design items and a relationship between the design items.”, the Examiner respectfully disagrees and asserts that Small et al., used as a secondary reference in the rejection, clearly provides that limitation; at para [0022], he states that the inputs provides to the module build layer image classification data generated by a convolutional neural network (640) configured to evaluate build layer images (630). The additive manufacture 2D post-process 720 may include a classification output 721. During development of an additive manufacturing process, an image of the classification output 721 at the appropriate depth may be directly related to an associated image of the additive manufacturing layer acquired in-process 723, which may provide a correlation/relationships between the in-process build layer image 630 and the post-process CNN classification output 721. [0080], As a result, a stored data record can be quickly retrieved using any known portion of the data that has been stored in that record by searching within that known datum's category within the database, and can be accessed by more complex queries, using languages such as Structured Query Language, which retrieve data based on limiting values passed as parameters and relationships between the data being retrieved. More specialized queries, such as image matching queries, may also be used to search some databases), and that the combination of the cited references clearly render obvious the limitations contrary to applicant’s assertions.
Claim Rejections - 35 USC § 101
5. 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.
5.1 Claims 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A- Prong One
The claim(s) recite(s) a manufacturing system design verification device, comprising means to perform steps of: “performing the query on the expression and returning an execution result” and “comparing the execution result with the expected result and returning a verification result”, wherein the design information corresponds to at least one of a mechanical design, an electrical design, a process design, and a control design, under the broadest reasonable interpretation fall under a mental process or otherwise a mathematical concept. Therefore, the claims are directed to an abstract idea, by use of generic computer components and thus are clearly directed to an abstract idea, as constructed.
Step 2A Prong Two
This judicial exception is not integrated into a practical application because the additional limitation such as: “a processor” to execute “a program”; and “a memory”, either alone or in combination, all serve to gather and process data and do not add anything more significantly to the judicial exception, but are mere instructions to apply the exception using a generic computer component that are well known, routine, and conventional activities (see specification at pages 5-6, and fig.1) which can be of any type, including general-purpose computer previously known in the industries. Merely adding a programmable computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice, 573 U.S. at 223-24. Furthermore, the use of a general-purpose computer to apply an otherwise ineligible algorithm does not qualify as a particular machine. See Ultramerciallnc. v. Hulu, LLC, 772F.3d 709, 716-17 (Fed. Cir. 20l4); In re TLI Commc 'ns LLC v. AV Automotive, LLC, 823 F.3d 607, 613 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept); Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785; the step of: “acquiring a design information model as a framework integrating and expressing design information, the design information model defining a class to classify design items and a relationship between the design items”; “inputting the design information and converting the design information into an expression described in a resource description language with reference to the design information model”, under the broadest reasonable interpretation, reasonable fall under data gathering and processing activities that are pre-solution activities” and the step of: “storing a verification logic including a group of a query described in a query language corresponding to the resource description language and an expected result” are also well-known, routine and conventional activities to store data in a memory and are not sufficient to amount to significantly more than the judicial exception (See further MPEP 2106.05(d)(i-iv)-f); thus are not patent eligible under 35 USC 101.
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as previously discussed above with reference to the integration of abstract idea into a practical application, the additional elements of: “a processor” to execute “a program”; and “a memory”, either alone or in combination, all serve to gather and process data and do not add anything more significantly to the judicial exception, but are mere instructions to apply the exception using a generic computer component that are well known, routine, and conventional activities (see specification at pages 5-6, and fig.1) which can be of any type, including general-purpose computer previously known in the industries. Merely adding a programmable computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice, 573 U.S. at 223-24. Furthermore, the use of a general-purpose computer to apply an otherwise ineligible algorithm does not qualify as a particular machine. See Ultramerciallnc. v. Hulu, LLC, 772F.3d 709, 716-17 (Fed. Cir. 20l4); In re TLI Commc 'ns LLC v. AV Automotive, LLC, 823 F.3d 607, 613 (Fed. Cir. 2016) (mere recitation of concrete or tangible components is not an inventive concept); Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785; the step of: “acquiring a design information model as a framework integrating and expressing design information, the design information model defining a class to classify design items and a relationship between the design items”; and “inputting the design information and converting the design information into an expression described in a resource description language with reference to the design information model”, under the broadest reasonable interpretation, reasonable fall under data gathering and processing activities that are pre-solution activities” and the step of: “storing a verification logic including a group of a query described in a query language corresponding to the resource description language and an expected result” are also well-known, routine and conventional activities to store data in a memory and are not sufficient to amount to significantly more than the judicial exception (See further MPEP 2106.05(d)(i-iv)-f); thus are not patent eligible under 35 USC 101. Therefore, using computer components amount to no more than mere instructions to perform the abstract, and thus are not sufficient to amount to significantly more than the recited abstract, as constructed.
5.2 Dependent claims 2-10 merely include limitations pertaining to further mathematical computations (claim 2), “inputting a verification item template including an input column for at least one of an external specification indicating a specification value of a manufacturing system and an internal specification indicating internal design information of the manufacturing system and generating the verification logic based on the verification item template” (data gathering and processing or otherwise a mental process). (claim 3); “inputting a verification item template including an input column for an operation specification expressing an operation of a manufacturing system and setting the operation specification to the verification logic, wherein simulatively executing a control program” (data gathering and processing) and “outputting an execution result using information included in the operation specification when the control program is inputted” (WURC post-solution activities), and “comparing the execution result outputted by the simulation execution environment with an expected result included in the operation specification” (a mental concept), and “returning a verification result” (post-solution activities); (claim 4); “storing the design information and including the design information in the design information which is accumulated” (WURC post-solution activities); “learning a design index from the design information which is accumulated”; and “generating the verification logic from the design index” (mental process); and the added claims 5-10 further do not recite anything that are sufficient to amount to significantly more than the already abstract but are all further amount mental process and/or data gathering and processing similar to that already recited by the independent claims and already addressed above and thus are further not patent eligible under 35 USC 101.
Claim Rejections - 35 USC § 103
6. 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.
6.0 Claim(s) 1-10 are rejected under 35 U.S.C. 103 as being unpatentable over Suzuki et al. (USPG_PUB No. 2016/0179084), in view of Small et al. (USPG_PUB No. 2018/0136633).
6.1 In considering claim 1, Suzuki et al. teaches a manufacturing system design verification device, comprising:
a processor to execute a program and a memory to store the program (see abstract, fig.1, para [0111]) which, when executed by the processor, performs processes of: acquiring a design information model as a framework integrating and expressing design information (see figure 18(S101), para [0042] The parameter value acquisition unit 71 acquires a value corresponding to the user-defined parameter name related to the component from the common parameter database 60 through the communication unit 21 when the line design processing unit 23 reads the line design information from the line design information storage unit 24. Further [0049], The line design information acquisition unit 52 acquires the line design information from the line design tool 20. [0063]); inputting the design information and converting the design information into an expression described in a resource description language with reference to the design information model (see fig.18 (s102), para [0044] The data format conversion unit 73 converts the value of the parameter acquired from the common parameter database 60 into a data format defined by the data format definition information in the data format definition information storage unit 72. [0065], The common parameter interface 70 is a program which enables each design tool to perform a process of reading the value associated with the parameter from the common parameter table 62 of the common parameter database 60, a process of converting the data format during the process of reading the value, and a process of changing the value associated with the parameter.); storing a verification logic including a group of a query expected result (see para [0087] FIG. 16 cache common parameter table in each design tool. The cache common parameter table includes a valid state indicating the validity or invalidity of each parameter and an update necessary/unnecessary state indicating whether the update of each parameter in the common parameter database 60 is required, in addition to the items of the common parameter table 62 illustrated in FIG. 4. [0075] Then, the common parameter change unit 64 updates the value of the acquired parameter name in the common parameter table 62 with the value stored in the change request (Step S55). Then, the common parameter change unit 64 transmits a parameter update completion notice to the design tool which has transmitted the change request (Step S56). In addition, the design tool receives the update completion notice from the common parameter database 60 (Step S57) and ends the parameter update process.); and performing the query on the expression and returning an execution result (see para [0102] Then, the parameter value acquisition unit 71 of the common parameter interface 70 acquires the valid state of data for a combination of the acquired control device and parameter, with reference to the cache common parameter table of the common parameter table temporary storage unit 25 (Step S95) and determines whether the data is valid (Step S96). When the data is valid (Yes in Step S96), the parameter value acquisition unit 71 acquires the value of the parameter from the cache common parameter table (Step S97). Further see [0109] When the parameter is updated, the common parameter table 62 of the host design tool is updated and the parameters of other design tools are updated. Then, it is notified or return the result notifying that the values stored in other design tools are valid. When the parameter is updated in a given design tool and the parameter reading process is performed in other design tools, a request to acquire the latest data of the parameter is transmitted to other design tools), wherein the design information corresponds to at least one of a mechanical design, an electrical design, a process design, and a control design (see para [0032] FIG. 1 is a block diagram schematically illustrating the configuration of a control system design support system according to the first embodiment. The control system design support system includes a design master database 10, a line design tool 20, a mechanical design tool 30, a control design tool 40, an interface generation device 50, and a common parameter database 60); however, he does not expressly show the design information model defining a class to classify design items and a relationship between the design items and the step of comparing the execution result with the expected result and returning a verification result. Small et al. teaches a method in which a computing device queries record stored in a database (see para [0080], a stored data record can be quickly retrieved using any known portion of the data that has been stored in that record by searching within that known datum's category within the database, and can be accessed by more complex queries, using languages such as Structured Query Language, which retrieve data based on limiting values passed as parameters and relationships between the data being retrieved. More specialized queries, such as image matching queries, may also be used to search some databases. A database can be created in any digital memory), wherein the design information model defining a class to classify design items and a relationship between the design items (see para [0022], inputting to the artificial intelligence module build layer image classification data generated by a convolutional neural network (640) configured to evaluate build layer images (630) captured in-process; inputting to the artificial intelligence module post-process image classification data generated by at least one other convolutional neural network (640) configured to evaluate images of a part captured post-process; and evaluating the additive manufacturing build parameter configuration files (830), the sequential time-based parameter data (714), the build layer image classification data (721), and the post-process image classification data by means of the artificial intelligence module; The additive manufacture 2D post-process 720 may include a classification output 721 (e.g., undermelt/just-right/overmelt) of a post-process 2D CNN evaluation 722 for part-quality classification. During development of an additive manufacturing process, an image of the classification output 721 at the appropriate depth may be directly related to an associated image of the additive manufacturing layer acquired in-process 723, which may provide a correlation between the in-process build layer image 630 and the post-process CNN classification output 721. [0080], As a result, a stored data record can be quickly retrieved using any known portion of the data that has been stored in that record by searching within that known datum's category within the database, and can be accessed by more complex queries, using languages such as Structured Query Language, which retrieve data based on limiting values passed as parameters and relationships between the data being retrieved. More specialized queries, such as image matching queries, may also be used to search some databases) and including the step of comparing the execution result with the expected result and returning a verification result (see para [0141] the resulting analysis and comparison 306 of hash functions 85 and 85a may yield three potential outcomes: By comparing the resulting hash created using the given inputs and the measured material composition 43, a resulting hash 85a that exactly matches the hash of the part 85 indicates that the part is genuine).
Suzuki et al. and Small et al. are analogous art because they are from the same field of endeavor and that that model analyzes by Small et al. is similar to that of Suzuki et al. Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
6.2 Regarding claim 2, the combined teachings of Suzuki et al. and Small et al. teaches the step of inputting a verification item template including an input column for at least one of an external specification indicating a specification value of a manufacturing system and an internal specification indicating internal design information of the manufacturing system and generating the verification logic based on the verification item template (see Suzuki fig.16 which a show input with specification for at least one value of manufacturing system, including verification results value and state in respective column; further para [0087] cache common parameter table in each design tool. The cache common parameter table includes a valid state indicating the validity or invalidity of each parameter and an update necessary/unnecessary state indicating whether the update of each parameter in the common parameter database 60 is required.). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
6.3 With regards to claim 3, the combined teachings of Suzuki et al. and Small et al. teaches the step inputting a verification item template including an input column for an operation specification expressing an operation of a manufacturing system and setting the operation specification to the verification logic (see Suzuki fig.16 which a show input with specification for at least one value of manufacturing system, including verification results value and state in respective column; further para [0034] The component 101 is, for example, a three-dimensional computer aided design (3D CAD) component of the control device, specification data of the control device, or a program component for controlling the operation of the control device. The line design parameter 1021 is used to operate the 3D CAD component with, for example, animation. The mechanical design parameter 1022 is used to create a timing chart. The control design parameter 1023 is used to input and output the program component. The line design parameter 1021, the mechanical design parameter 1022, and the control design parameter 1023 have the same meaning but have different formats), wherein simulatively executing a control program and outputting an execution result using information included in the operation specification when the control program is inputted, (see Suzuki et al. para [0034], The control design parameter 1023 is used to input and output the program component. The line design parameter 1021, the mechanical design parameter 1022, and the control design parameter 1023 have the same meaning but have different formats. [0060] The control design tool 40 generates or changes operation parameters and a control program, which is the control design information, from the content input by the user, on the basis of the mechanical design information. The control program defines a program executed by the control device. FIG. 8 is a block diagram schematically illustrating an example of the functional configuration of the control design tool. The control design tool 40 includes a communication unit 41, an input unit 42, a control design processing unit 43, a control program storage unit 44, and the common parameter interface 70.) and comparing the execution result outputted by the simulation execution environment with an expected result included in the operation specification, and returning a verification result (see Small et al. para [0141] the resulting analysis and comparison 306 of hash functions 85 and 85a may yield three potential outcomes: By comparing the resulting hash created using the given inputs and the measured material composition 43, a resulting hash 85a that exactly matches the hash of the part 85 indicates that the part is genuine). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
6.4 Regarding claim 4, the combined teachings of Suzuki et al. and Small et al. teaches the step storing the design information and including the design information in the design information which is accumulated (see Suzuki et al. para [0087] FIG. 16 cache common parameter table in each design tool. The cache common parameter table includes a valid state indicating the validity or invalidity of each parameter and an update necessary/unnecessary state indicating whether the update of each parameter in the common parameter database 60 is required, in addition to the items of the common parameter table 62 illustrated in FIG. 4. [0075] Then, the common parameter change unit 64 updates the value of the acquired parameter name in the common parameter table 62 with the value stored in the change request (Step S55). Then, the common parameter change unit 64 transmits a parameter update completion notice to the design tool which has transmitted the change request (Step S56). In addition, the design tool receives the update completion notice from the common parameter database 60 (Step S57) and ends the parameter update process.); learning a design index from the design information which is accumulated (see Small et al. para [0188] Referring now to FIG. 38, operation of a deep learning process controller 900 for additive manufacture machine 530 is illustrated. The system comprises a closed-loop control structure 910, 920 for adjusting the initial set of build parameters 830 in-process. The deep learning process controller 900 may be a hybrid of an advanced non-linear stochastic control and a complex adaptive model-based control as may be implemented by the trained deep learning recurrent artificial intelligence (AI) module 850.) ; and generating the verification logic from the design index (Small et al. para [0191] In fast control loop 920, melt pool data 712 may be inputted to state machine 840 along with output from trained deep learning AI module 850. A state machine output from trained deep learning AI module 850 may be used as part of the fast control loop 920, which may be configured as a separate state-variable inner control loop on the fast process control gain update. For example, a state machine output from a long short-term memory (LSTM), as described below, may be inputted to state machine 840 and used to facilitate fast-loop closure of the melt pool control). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
6.5 Regarding claim 5, the combined teachings of Suzuki et al. and Small et al. teaches that wherein the resource description language is a Resource Description Framework (RDF) or an AutomationML (see Suzuki et al. para [0057], In this example, the ID, the user-defined parameter name in the line design information, the user-defined parameter name in the mechanical design information, and the user-defined parameter name in the control program are associated with the parameter name in the common parameter table 62. In addition, in this example, the common parameter table 62 and the parameter association table 63 are managed in a table format. For example, the common parameter table 62 and the parameter association table 63 may be managed, using a markup language such as an extensible markup language (XML). Small et al. para [0080], As a result, a stored data record can be quickly retrieved using any known portion of the data that has been stored in that record by searching within that known datum's category within the database, and can be accessed by more complex queries, using languages such as Structured Query Language, which retrieve data based on limiting values passed as parameters and relationships between the data being retrieved.). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
6.6 As per claim 6, the combined teachings of Suzuki et al. and Small et al. teaches that wherein the query language is SPARQL see Suzuki et al. para [0057], In this example, the ID, the user-defined parameter name in the line design information, the user-defined parameter name in the mechanical design information, and the user-defined parameter name in the control program are associated with the parameter name in the common parameter table 62. In addition, in this example, the common parameter table 62 and the parameter association table 63 are managed in a table format. For example, the common parameter table 62 and the parameter association table 63 may be managed, using a markup language such as an extensible markup language (XML). Small et al. para [0080], As a result, a stored data record can be quickly retrieved using any known portion of the data that has been stored in that record by searching within that known datum's category within the database, and can be accessed by more complex queries, using languages such as Structured Query Language, which retrieve data based on limiting values passed as parameters and relationships between the data being retrieved. ). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
6.7 Regarding claim 7, the combined teachings of Suzuki et al. and Small et al. teaches that wherein the expected result is expressed by a function definition outputting a truth-value taking the execution result of the query as an argument using a programming language see Suzuki et al. para [0057], In this example, the ID, the user-defined parameter name in the line design information, the user-defined parameter name in the mechanical design information, and the user-defined parameter name in the control program are associated with the parameter name in the common parameter table 62. In addition, in this example, the common parameter table 62 and the parameter association table 63 are managed in a table format. For example, the common parameter table 62 and the parameter association table 63 may be managed, using a markup language such as an extensible markup language (XML). 0086] The common parameter table temporary storage unit 25 temporarily stores a common parameter table 62 acquired from the common parameter database 60. Hereinafter, the common parameter table stored in the common parameter table temporary storage unit 25 is referred to as a cache common parameter table. [0087] The cache common parameter table includes a valid state indicating the validity or invalidity of each parameter and an update necessary or unnecessary state indicating whether the update of each parameter in the common parameter database 60 is required, in addition to the items of the common parameter table 62 illustrated in FIG. 4. Further see Small et al. para [0080], a stored data record can be quickly retrieved using any known portion of the data that has been stored in that record by searching within that known datum's category within the database, and can be accessed by more complex queries, using languages such as Structured Query Language, which retrieve data based on limiting values passed as parameters and relationships between the data being retrieved.). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
6.8 As per claim 8, the combined teachings of Suzuki et al. and Small et al. teaches that wherein the verification result is included in a verification result list and outputted to a user via a graphical user interface (see Small et al. para [0192], The evaluation result provided by CNN 640, which may indicate a degree to which each captured layer image 630 corresponds to an expected or desired appearance of the layer, is used in block 610 to calculate adjusted build parameters of additive manufacturing machine 530 in-process to influence building of subsequent layers as the build process continues in block 620. The evaluation result may be in the form of an assigned classification of each build layer image 630 into a predetermined category (e.g. very good, good, fair, bad, etc.)). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
6.9 As per claim 9, the combined teachings of Suzuki et al. and Small et al. teaches that wherein the design information storage part stores both the inputted design information and a design information resource obtained by converting the design information in a design information database (see Suzuki et al. para [0041], The common parameter interface 70 includes a data format definition information storage unit 72, a data format conversion unit 73, and a parameter update unit 74. [0042] The parameter value acquisition unit 71 acquires a value corresponding to the user-defined parameter name related to the component from the common parameter database 60 through the communication unit 21 when the line design processing unit 23 reads the line design information from the line design information storage unit 24. [0043] The data format definition information storage unit 72 stores data format definition information for defining the data format required when the value of the parameter acquired by the parameter value acquisition unit 71 is treated in the line design tool 20. [0044] The data format conversion unit 73 converts the value of the parameter acquired from the common parameter database 60 into a data format defined by the data format definition information in the data format definition information storage unit 72. Further Small et al. para [0084], For instance, the computing device may protect data using a cryptographic system. In one embodiment, a cryptographic system is a system that converts data from a first form, known as “plaintext,” which is intelligible when viewed in its intended format, into a second form, known as “cyphertext,” which is not intelligible when viewed in the same way. The cyphertext is unintelligible in any format unless first converted back to plaintext. In one embodiment, the process of converting plaintext into cyphertext is known as “encryption.” The encryption process may involve the use of a datum, known as an “encryption key,” to alter the plaintext. The cryptographic system may also convert cyphertext back into plaintext, which is a process known as “decryption.). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
6.10 With regards to claim 10, the combined teachings of Suzuki et al. and Small et al. teaches that wherein the verification is performed when the design information is updated or when the verification logic is updated in accordance with an update of the design information model (see Suzuki et al. para [0075] Then, the common parameter change unit 64 updates the value of the acquired parameter name in the common parameter table 62 with the value stored in the change request (Step S55). Then, the common parameter change unit 64 transmits a parameter update completion notice to the design tool which has transmitted the change request (Step S56). In addition, the design tool receives the update completion notice from the common parameter database 60 (Step S57) and ends the parameter update process. Small et al. para [0024], the trained artificial intelligence module is trained using evaluation data from a first convolutional neural network (640) configured to evaluate layer images acquired in-process, and at least one second convolutional neural network (640) configured to evaluate images of finished parts acquired post-process; the at least one second convolutional neural network (640) includes a convolutional neural network (640) configured to evaluate two-dimensional images of sectioned parts; the at least one second convolutional neural network (640) includes a convolutional neural network (640) configured to evaluate three-dimensional images of parts (732); the trained artificial intelligence module (850) is a deep learning module having a recurrent artificial neural network). Therefore, it would have been obvious to a person of skilled in the art at the time of filing of the applicant’s invention to combine the method of Small et al. with that of Suzuki et al. because Small et al. teaches the improvement of quality (see para [0188]).
Conclusion
7. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
7.1 Chen et al. (USPG_PUB No. 2020/0401650) teaches automating solving non-deterministic polynomial-time (NP) problems in annealer systems.
8. Claims 1-10 are rejected and THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDRE PIERRE-LOUIS whose telephone number is (571)272-8636. The examiner can normally be reached M-F 9:00 AM-5:00 PM.
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/ANDRE PIERRE LOUIS/Primary Patent Examiner, Art Unit 2187 December 13, 2025
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