DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of the Claims
Claims 1-20 were previously pending and subject to a non-final rejection dated October 1, 2025. In the Response, submitted on December 31, 2025, claims 1, 7, 12 and 17 were amended, claims 5-6 and 16 were cancelled, and claims 21-23 were added. Therefore, claims 1-4, 7-15, and 17-23 are currently pending and subject to the following final rejection.
Response to Arguments
Applicant’s Remarks on Pages 10-12 of the Response, regarding the previous rejection of the claims under 35 U.S.C. 101 have been fully considered but are not found persuasive.
On Page 10 of the Response, Applicant argues “that the steps of automatically initiating at least one of one or more device component repair operations and one or more device component replacement operations is a physical technical set of actions, plainly distinct from ‘commercial interactions.’”
Examiner respectfully disagrees and notes as explained in Para. [0073] of Applicant’s PG Publication, “…performing one or more automated actions includes automatically generating and outputting at least one recommendation, to one or more component repair technicians and/or systems, in connection with the at least one of the one or more device components predicted as needing to be at least one of repaired and replaced” and Para. [0066] explains that “such recommendations and/or predictions can be used to initiate one or more automated actions (e.g., automatically initiating one or more device component repair operations, automatically initiating one or more device component replacement operations, automatically retraining the model used to generate the recommendations and/or predictions, etc.).”. However, Para. [0066] and other portions of the specification are silent on what constitutes the repair or replacement operations. For example, under broadest reasonable interpretation, “automatically intitiating….at least one of…component repair operations…and…device component replacement operations” includes ordering a device component part/submitting purchase order. Therefore, in light of the specification (See Para. [0003] explaining that the disclosure “provide techniques for predicting device components for repair and/or replacement…”) Examiner notes that “the steps of automatically initiating at least one of one or more device component repair operations and one or more device component replacement operations” reflect the abstract idea of a certain method of organizing human activity (e.g., commercial interaction).
On Pages 11-12 of the Response, in analogizing the claims to those of Ex Parte Desjardins, Applicant argues “claims 1, 12 and 17 clearly integrate the abstract idea into a practical application that provide improvement sin computer technology” and cites to portions of Applicant’s specification discussing “the models…may be trained to generate recommendations and/or predictions… such recommendations and/or predictions can be used to initiate one or more automated actions (e.g., automatically initiating one or more device component repair operations, automatically initiating one or more device component replacement operations, automatically retraining the model used to generate the recommendations and/or predictions, etc.)… this ranked output can be leveraged by one or more technicians and/or automated systems as a guide towards selecting the correct and/or appropriate device component(s) to be repaired and/or replaced according to the issue description(s).”
Examiner respectfully disagrees and firstly notes, as discussed above, the specification is silent on what constitutes the repair or replacement operations. Second, Examiner respectfully disagrees that Applicant’s claims are similar to those of Ex Parte Desjardins, and notes that the mere recitation of “automatically training at least a portion of the one or more artificial intelligence techniques using feedback” in claim 11 is not similar to the specification identified improvements as to how the machine learning model itself operates of Ex Parte Desjardins. Specifically, the specification identified the improvement to machine learning technology by explaining how the machine learning model is trained to learn new tasks while protecting knowledge about previous tasks to overcome the problem of “catastrophic forgetting,” and that the claims reflected the improvement identified in the specification. Thus, Applicant’s arguments are not found persuasive.
Examiner recommends Applicant amendment their claims more similarly to those in Ex Parte Desjardins, indicating support in the specification for the identified improvements.
Applicant’s Remarks on Pages 12-14 of the Response, regarding the previous rejection of the claims under 35 U.S.C. 103 have been fully considered and are found persuasive in view of the amended claims.
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 1-4, 7-15 and 17-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-4, and 7-11 recite a method (i.e., a process), claims 12-15 recite a non-transitory computer readable storage medium (i.e., a machine); and claims 17-23 recite an apparatus comprising at least one processing device comprising a process (i.e., a machine). Therefore the claims all fall within one of the four statutory categories of invention.
Step 2A, Prong One
Claims 1, 12 and 17 recite the steps/functions of: obtaining information pertaining to at least one device defect; defining multiple device component categories related to the at least one device defect; determining one or more of the multiple device component categories as associated with the at least one device defect by processing at least a first portion of the obtained information; identifying one or more device components associated with at least a second portion of the obtained information; predicting at least one of the one or more device components associated with the at least a second portion of the obtained information, based at least in part on comparing (i) the one or more device components associated with the at least a second portion of the obtained information and (ii) the one or more device component categories associated with the at least one device defect, as needing to be at least one of repaired and replaced in connection with at least a portion of the at least one device defect, wherein predicting at least one of the one or more device components as needing to be at least one of repaired and replaced comprises: determining one or more intersections between descriptions of device components associated with the one or more determined device component categories and descriptions of the one or more device components associated with the at least a second portion of the obtained information and ranking at least a portion of the one or more intersections based at least in part on a number of one or more terms shared across the at least a portion of the one or more intersections; and performing actions based at least in part on the predicting of the at least one of the one or more device components as needing to be at least one of repaired and replaced, wherein performing actions comprises initiating, in conjunction with the ranking of the at least a portion of the one or more intersections, at least one of one or more device component repair operations and one or more device component replacement operations.
The claims as a whole recites a certain method of organizing human activity. The limitations recited above, under broadest reasonable interpretation, recite the abstract idea of a certain method of organizing human activity, e.g., commercial interactions. Therefore, the claims recite an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. Claims 1, 12 and 17 as a whole amount to: “apply it” (or an equivalent) with the judicial exception, or merely include instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea.
The claims recite the additional elements of: (i) at least one processing device comprising a processor coupled to a memory (claims 1 and 17), (ii) a non-transitory processor-readable storage medium having stored therein program code of one or more software programs, wherein the program code when executed by at least one processing device causes the at least one processing device to perform a method (claim 12), (iii) using one or more artificial intelligence techniques (claims 1, 12, and 17), and (iv) performing one or more automated actions, automatically initiating, using one or more automated systems (claims 1, 12, and 17).
The additional elements listed above, are recited at a high-level of generality such that, when viewed as whole/ordered combination, they each amount to no more than mere instructions to apply the judicial exception using generic computer components (See MPEP 2106.05(f)).
Accordingly, these additional elements, when viewed as a whole/ordered combination (See Fig. 13) do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, claims 1 and 9 are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements in claims 1, 12, and 17 amount to no more than reciting the words “apply it” (or an equivalent) with the judicial exception, or merely include instructions to implement an abstract idea on a computer, or merely use a computer as a tool to perform an abstract idea; or generally link the use of a judicial exception to a particular technological environment or field of use. The same analysis applies here in 2B, i.e., reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional elements discussed above do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claims add significantly more (i.e., an inventive concept) to the abstract idea. Thus, claims 1, 12, and 17 are ineligible.
Dependent claims 2-4, 7, 13-14, 16 and 18-21 further recite details which merely narrow the previously recited abstract idea limitiaitions. For these reasons, as described above with respect to claims 1, 12, and 17 respectively, these judicial exceptions are not meaningfully integrated into a practical application or significantly more than the abstract idea. Thus, claims 2-4, 7, 13-14, 16 and 18-21 are also ineligible.
Claims 8 and 22 recite wherein determining one or more of the multiple device component categories as associated with the at least one device defect comprises processing the at least a first portion of the obtained information - which narrows the previously recited abstract idea. The additional element unencompassed by the abstract idea includes using at least one long short-term memory (LSTM) model. The abstract idea is not integrated into a practical application because the additional element generally links the use of a judicial exception to a particular technological environment or field of use (i.e., neural network). See MPEP 2106.05(h).
The claims do not include limitations sufficient, either alone or in combination, to amount to significantly more than the claimed abstract idea because the aforementioned additional element generally links the use of a judicial exception to a particular technological environment or field of use (i.e., neural network). See MPEP 2106.05(h).
Claims 9 and 23 recite wherein determining one or more of the multiple device component categories as associated with the at least one device defect comprises processing the at least a first portion of the obtained information - which narrows the previously recited abstract idea. The additional element unencompassed by the abstract idea includes using at least one transformers-based model. The abstract idea is not integrated into a practical application because the additional element generally links the use of a judicial exception to a particular technological environment or field of use (i.e., neural network). See MPEP 2106.05(h).
The claims do not include limitations sufficient, either alone or in combination, to amount to significantly more than the claimed abstract idea because the aforementioned additional element generally links the use of a judicial exception to a particular technological environment or field of use (i.e., neural network). See MPEP 2106.05(h).
Claim 10 recites wherein determining one or more of the multiple device component categories as associated with the at least one device defect comprises processing the at least a first portion of the obtained information using at least one clustering algorithm - which narrows the previously recited abstract idea. The additional element unencompassed by the abstract idea includes processing the at least a first portion in conjunction with one or more deep learning techniques. The abstract idea is not integrated into a practical application because the additional element generally links the use of a judicial exception to a particular technological environment or field of use (i.e., neural network). See MPEP 2106.05(h).
The claim does not include limitations sufficient, either alone or in combination, to amount to significantly more than the claimed abstract idea because the aforementioned additional element generally links the use of a judicial exception to a particular technological environment or field of use (i.e., neural network). See MPEP 2106.05(h).
Claim 11 recites using feedback related to the predicting of the at least one of the one or more device components as needing to be at least one of repaired and replaced – which narrows the previously recited abstract idea.
The additional element unencompassed by the abstract idea includes performing one or more automated actions comprising automatically training at least a portion of the one or more artificial intelligence techniques. The abstract idea is not integrated into a practical application because the additional element generally links the use of a judicial exception to a particular technological environment or field of use (i.e., training artificial intelligence). See MPEP 2106.05(h).
The claim does not include limitations sufficient, either alone or in combination, to amount to significantly more than the claimed abstract idea because the aforementioned additional element generally links the use of a judicial exception to a particular technological environment or field of use (i.e., training artificial intelligence). See MPEP 2106.05(h).
Allowable over the Prior Art
The claims are allowable over the prior art but subject to the above rejection under 35 U.S.C. 101.
Examiner notes the closest prior art for the independent claims includes: U.S. Patent Application Publication No. 2016/0069778 to Sahu (hereinafter “Sahu”). Sahu discloses while servicing a machine, expert technicians may try to apply domain knowledge expertise, which can be described as expert knowledge in the field, to predict whether a different component is on the verge of failure and should also be repaired or replaced. By levering data mining by discovering sequences of frequent itemsets (referring to component failures that occur together), a processor generates (outputs) recommendations of which associated components should be serviced, based on historic repair data stored within a database.
U.S. Patent Application Publication No. 2019/0156298 to Ethington et al. (hereinafter “Ethington”). Ethington discloses a data processing system that categorizes a plurality of systems into clusters using an unsupervised machine learning method to analyze repair data parameters of a historical dataset relating to the plurality of systems.
U.S. Patent Application Publication No. 2015/0269153 to Fink et al. (hereinafter “Fink”). Fink discloses a summary application may then include in the summary frequently correlated related entities along and associated text phrases that are semantically important. Semantically important text phrases may be ranked, and wherein ranking associated text phrases is performed using text analytics.
CN116134394 to Grishna et al. (hereinafter “Grishna”). Grishna discloses querying a knowledge base of maintenance cases using a text query to retrieve a ranked list of maintenance cases related to the text query; performing topic modeling on the maintenance cases of the ranked list of maintenance cases to group the maintenance cases into N topics; ranking, for each topic, the replaced part identifiers associated with the maintenance cases grouped into that topic to generate a ranked list of replaced part identifiers for that topic; and displaying a list of recommended parts for replacement including at least a top portion of the ranked list of replaced part identifiers for the selected subject matter.
Prior Art
The following is prior art not cited but considered relevant:
U.S. Patent Application Publication No. 2022/0026895 to Leitch et al. (hereinafter “Leitch”). Leitch discloses evaluating the correlation between each of a plurality of operational data features and maintenance events of the maintenance data, using a supervised machine learning classification model.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/RUPANGINI SINGH/Primary Examiner, Art Unit 3628