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 .
Response to Amendment
The amendment filed on 2/10/2026 has been entered. Claims 1-20 remain pending in the present application. Applicant’s amendments to the claims have not overcome the 35 U.S.C. 101 rejection set forth previously.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards an abstract idea without significantly more. Claim 1 recites: “determining an engineering process to be performed on a workpiece, wherein the engineering process has one or more engineering process elements associated with one of an assembly process or a maintenance process for the workpiece;”, “causing the at least one AI model to process the sensor data to generate at least one classification result, wherein the at least one classification result indicates whether the sensor data indicates whether each engineering process element of the one or more engineering process elements was correctly performed;”, “wherein the at least one AI model is validated to correctly recognize, at or above a predetermined threshold, all validation data for each of the one or more engineering process elements”,, “validating execution of the engineering process in response to each engineering process element of the one or more engineering process elements being correctly performed;”, and “certifying execution of the engineering process as having been completed according to requirements of the engineering process and in response to validation of the execution of the engineering process,”, which analyzed under Step 2A Prong One, includes limitations of determining a process to be performed on a workpiece, identifying it was done correctly, validating an AI model analysis of steps compared to thresholds, validating each step was performed based on received data, and certifying that the validation was performed which are limitations which can all reasonably be performed in the human mind which fall within the “Mental Processes” grouping of abstract ideas.
This judicial exception is not integrated into a practical application. For instance, claim 1 further recites, “providing a visual notification to a user that the execution of the engineering process has been validated.”, which analyzed under Step 2A Prong Two, just simply provides a notification to a user which just merely applies the use of the judicial exception (see MPEP 2106.05(f)). Further, claim 1 recites, “receiving sensor data from one or more sensors associated with the workpiece, the sensor data reflecting at least a physical state of the workpiece;”, “providing the sensor data to the at least one AI model;”, and “wherein certifying the execution of the engineering process comprises providing certification data indicating that the workpiece is ready for service, and further comprises storing validation information regarding validation of execution of the engineering,” which analyzed under Step 2A Prong Two, adds insignificant extra solution activity in the form of mere data gathering (see MPEP 2106.05(g)). Finally, the limitations of, “at least one processor” and “a non-transitory computer readable medium”, as generally recited represent merely generic computer components for implementing the abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because as analyzed under Step 2B, the additional elements merely amount to gathering engineering process performance data and sending the data over a network. Analyzed under Berkheimer, the act of gathering and sending data over a network has been deemed as well-understood, routine, and conventional by the courts (see MPEP 2106.05(d)(II), “sending/receiving data over a network”).
Claims 9 and 17 are substantially similar to claim 1 and are thus rejected using the same rationale as provided above.
Claims 2-8, 10-16, and 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards an abstract idea without significantly more. For instance, claims 6-8, 14-16, and 19-20, each include limitations of validating work, identifying/validating parts, or validating part location, usage, placement, which analyzed under Step 2A Prong One, are all limitations which can reasonably be performed in the human mind and thus fall within the, “Mental Processes” grouping of abstract ideas.
This judicial exception is not integrated into a practical application. Claims 5, 13, and 18, each include limitations of displaying results to a user, which analyzed under Step 2A Prong two, just merely applies the use of the judicial exception. Claim 4 discloses elements of transferring data, which analyzed under Step 2A Prong Two, adds insignificant extra solution activity in the form of mere data gathering (see MPEP 2106.05(g)). Finally, claims 2-4 and 10-12, describe various limitations detailing what the engineering elements comprise of, technician actions, type of data validated, types of sensor data monitored during manipulation of a work piece, and what data is used when generating a classification which analyzed under Step 2A Prong Two, provide limitations which provide general descriptions of various elements without providing inventive steps and thus just generally link the use of the judicial exception to a particular technological environment or field of use (see MPEP 2106.05(h)).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as analyzed under Step 2B, the additional elements merely amount to gathering engineering process performance data and sending the data over a network. Analyzed under Berkheimer, the act of gathering and sending data over a network has been deemed as well-understood, routine, and conventional by the courts (see MPEP 2106.05(d)(II), “sending/receiving data over a network”).
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1 and 3-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Greco et al. (US PGPUB 20220301266).
Regarding Claims 1, 9, and 17; Greco teaches; A system, comprising:
at least one processor; and (Greco; at least Fig. 1; processor (104))
a non-transitory computer readable medium connected to the processor and having at least one artificial intelligence (AI) model stored therein, and further having a computer program for execution by the processor stored therein, the computer program including instructions for: (Greco; at least Figs. 1, 4, and 6; paragraphs [0002] and [0016]; disclose data storage device (106) which includes a plurality of machine learning models which are used in conjunction with augmented reality to receive visual/audio input and generate output instructions that are presented to the user’s augmented reality display to aid in performing tasks)
determining an engineering process to be performed on a workpiece, wherein the engineering process has one or more engineering process elements associated with one of an assembly process or a maintenance process for the workpiece; (Greco; at least Fig. 4; paragraphs [0055] and [0071]; disclose wherein the system and method includes making a determination as to whether an assembly step is to take place)
receiving sensor data from one or more sensors associated with the workpiece, the sensor data reflecting at least a physical state of the workpiece; (Greco; at least Fig. 6; paragraph [0075]; disclose wherein the system and method includes taking video and audio data of the object being worked on which provides a reflection of the physical state of the object)
providing the sensor data to the at least one AI model; (Greco; at least Fig. 6; paragraph [0076]; disclose providing the audio/visual sensor data to a machine learning model for review)
causing the at least one AI model to process the sensor data to generate at least one classification result, wherein the at least one classification result indicates whether the sensor data indicates whether each engineering process element of the one or more engineering process elements was correctly performed, wherein the at least one AI model is validated to correctly recognize, at or above a predetermined threshold, all validation data for each of the one or more engineering process elements; (Greco; at least Fig. 6; paragraphs [0060] and [0076]-[0077]; disclose wherein the machine learning model can process the sensor data and make a determination if the assembly was done correctly or incorrectly, wherein further, the system includes comparing each inspection step to confidence level threshold which can signal further as to whether a step was correctly performed based compared to the confidence level threshold)
validating execution of the engineering process in response to each engineering process element of the one or more engineering process elements being correctly performed; and (Greco; at least Figs. 3-4 and 6; paragraphs [0076]-[0077] and [0081]; disclose wherein the system and method includes validating each step and iterates until it determines that all procedural steps have been completed)
certifying execution of the engineering process as having been completed according to requirements of the engineering process and in response to validation of the execution of the engineering process, wherein certifying the execution of the engineering process comprises providing certification data indicating that the workpiece is ready for service, and further comprises storing validation information regarding validation of execution of the engineering process and further regarding verification that the engineering process was performed correctly; (Greco; at least paragraphs [0069] and [0085]; disclose wherein the system includes validating each step until no error has been detected, once complete, the system then stores that step as complete (i.e. certifies) in the progress of the steps to complete, and then subsequently allows continuing on to the next step in the maintenance process. Certification is further demonstrated in paragraph [0085] in which the system includes inspection of four tires, but only certifies when it confirms that in fact all four tires were inspected and not just a single tire four times)
providing a visual notification to a user that the execution of the engineering process has been validated. (Greco; at least paragraphs [0078] and [0083]; disclose wherein the results of a successfully completed assembly task is displayed).
Regarding Claims 3 and 11; Greco teaches; The system of claim 2, wherein the first engineering process element comprises a step of at least one of a technician manipulating at least a part of the workpiece according to a specified parameter, or a technician manipulating at least a part of the workpiece using a specified tool. (Greco; at least paragraphs [0076] and [0077]).
Regarding Claim 4; Greco teaches; The system of claim 1, wherein the computer program further includes instructions for providing validation information to a storage system, wherein the validation information is associated with at least one of verification that the engineering process was performed correctly, tracking of maintenance, tracking of parts, or tracking of health history. (Greco; at least Figs. 4 and 6; paragraphs [0076]-[0077]).
Regarding Claims 5 and 13; Greco teaches; The system of claim 1, wherein the computer program further includes instructions for providing engineering process data associated with the engineering process to a display, the engineering process data causing the display to display a graphic representation of a list of sub processes and engineering process elements associated with the engineering process. (Greco; at least paragraph [0072]).
Regarding Claims 6, 14, and 19; Greco teaches; The system of claim 1, wherein a first AI model of the least one AI model is an object recognition model, and wherein the instructions for causing the at least one AI model to process the sensor data include instructions for causing the first AI model to perform object recognition on the sensor data. (Greco; at least paragraphs [0037]-[0038]).
Regarding Claims 7 and 15; Greco teaches; The system of claim 6, wherein the instructions for causing the first AI model to perform object recognition comprise instructions for causing the first AI model to perform: identifying a part of interest; and validating the part of interest. (Greco; at least Fig. 3; paragraphs [0037]-[0038] and [0077]-[0078]).
Regarding Claims 8 and 16; Greco teaches; The system of claim 7, wherein the instructions for causing the first AI model to perform object recognition further comprise instructions for causing the first AI model to perform: validating at least one of a part location, a part usage, or part placement, of the part of interest. (Greco; at least paragraphs [0077]-[0078]).
Regarding Claim 10; Greco teaches; The system of claim 9, wherein a first engineering process element of the one or more engineering process elements comprises a step of manipulating at least a part of the workpiece. (Greco; at least paragraphs [0076] and [0077]).
Regarding Claim 18; Greco teaches; The system of claim 17, further comprising a display; wherein the at least one processing circuit is further configured for providing engineering process data associated with the engineering process to the display, the engineering process data causing the display to display a graphic representation of at least a portion of the plurality of engineering process elements. (Greco; at least paragraph [0072]).
Regarding Claim 20; Greco teaches; The system of claim 19, wherein the at least one processing circuit being configured for causing the first AI model to perform object recognition comprises the at least one processing circuit being configured for causing the first AI model to perform: identifying a part of interest; validating the part of interest; and validating at least one of a part location, a part usage, or part placement, of the part of interest. (Greco; at least Fig. 3; paragraphs [0037]-[0038] and [0077]-[0078]).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Greco et al. (US PGPUB 20220301266) in view of Buras et al. (US PGPUB 20200135055).
Regarding Claim 2; Greco teaches; The system of claim 1, wherein a first engineering process element of the one or more engineering process elements comprises a step of manipulating at least a part of the workpiece, (Greco; at least paragraphs [0076] and [0077]).
Greco appears to be silent on; wherein the sensor data reflects the physical state of the workpiece during manipulation of the at least the part of the workpiece during performance of the first engineering process element, and wherein the sensor data further reflects at least one of an action or gesture performed as part of manipulation of the at least the part of the workpiece during performance of the first engineering process element and wherein the causing the at least one AI model to process the sensor data to generate at least one classification result comprises causing the at least one AI model to generate the classification result according to the sensor data that reflects the physical state of the workpiece during manipulation of the at least the part of the workpiece during performance of the first engineering process element, and further according to the sensor data that reflects the at least one of the action or gesture performed as part of the manipulation of the at least the part of the workpiece during performance of the first engineering process element.
However, Buras teaches; wherein the sensor data reflects the physical state of the workpiece during manipulation of the at least the part of the workpiece during performance of the first engineering process element, and wherein the sensor data further reflects at least one of an action or gesture performed as part of manipulation of the at least the part of the workpiece during performance of the first engineering process element and wherein the causing the at least one AI model to process the sensor data to generate at least one classification result comprises causing the at least one AI model to generate the classification result according to the sensor data that reflects the physical state of the workpiece during manipulation of the at least the part of the workpiece during performance of the first engineering process element, and further according to the sensor data that reflects the at least one of the action or gesture performed as part of the manipulation of the at least the part of the workpiece during performance of the first engineering process element. (Buras; at least paragraphs [0011]-[0013]; disclose an AR assisted procedure method in which the system includes using sensors to detect various gestures and positioning of equipment by a user during performance of a procedure, wherein the method can determine resulting classifications based on the detected measurements and further provide corrective actions within the AR system if it detects the gestures/positioning by the user is off).
Greco and Buras are analogous art because they are from the same field of endeavor or similar problem solving area of, AR assisted control systems and methods.
It would have been obvious to one of ordinary skill in the art before the effective filing date to have incorporated the known method of real-time positioning/gesture detection during a procedure as taught by Buras with the known system of an AR assisted maintenance monitoring and control system as taught by Greco in order to help provide feedback and guide novice level user’s during a potential unfamiliar task as taught by Buras (paragraph [0010]).
Response to Arguments
Applicants’ arguments filed 2/10/2026 have been fully considered but they are not persuasive.
Applicant argues:
That the claims have been amended to include providing sensor data to an AI and using the AI to process and classify the data which cannot be done mentally.
The reference of Greco is silent on comparing validation to a threshold nor do they teach providing certification of results.
With regards to the first argument, simply using AI to perform a task does not inherently mean that it cannot be performed in the human mind. For instance, at face value, the tasks performed by the AI model as currently claim are:
reviewing sensor data detailing physical aspects of a workpiece
classifying whether a process was done correctly by comparing the sensor data to a threshold
The office argues, without context, reviewing sensor data and comparing it to a threshold to make a determination on how to classify whether the object was operated on correctly is something that is more than reasonable to perform in the human mind. Without detail as to why the particular data is impossible to review by a human that can then make a judgement, the office argues that the present claims represent a “Mental Process” abstract idea.
Further, incorporating the additional limitations merely amount collecting, analyzing, and displaying results which, per the MPEP 2106.04(a)(2)(III)(A), has been determined by the courts to represent a Mental Process Abstract idea as presented below:
“A Claim With Limitation(s) That Cannot Practically be Performed in the Human Mind Does Not Recite a Mental Process[AltContent: rect]
Claims do not recite a mental process when they do not contain limitations that can practically be performed in the human mind, for instance when the human mind is not equipped to perform the claim limitations. See SRI Int’l, Inc. v. Cisco Systems, Inc., 930 F.3d 1295, 1304 (Fed. Cir. 2019) (declining to identify the claimed collection and analysis of network data as abstract because "the human mind is not equipped to detect suspicious activity by using network monitors and analyzing network packets as recited by the claims"); CyberSource, 654 F.3d at 1376, 99 USPQ2d at 1699 (distinguishing Research Corp. Techs. v. Microsoft Corp., 627 F.3d 859, 97 USPQ2d 1274 (Fed. Cir. 2010), and SiRF Tech., Inc. v. Int’l Trade Comm’n, 601 F.3d 1319, 94 USPQ2d 1607 (Fed. Cir. 2010), as directed to inventions that ‘‘could not, as a practical matter, be performed entirely in a human’s mind’’).
In contrast, claims do recite a mental process when they contain limitations that can practically be performed in the human mind, including for example, observations, evaluations, judgments, and opinions. Examples of claims that recite mental processes include:[AltContent: rect]
• a claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);
With regards to the second argument, the office points to the 102 rejection above for support of the newly amended limitations. But in brief, Greco describes providing a confidence threshold for validating each of the process steps performed during the maintenance process in paragraph [0060] and further, in paragraphs [0069] and [0085], describe certifying validation in several ways including only saving (certifying) progress once the validation is confirmed and further provides an example of certifying that the task is complete by ensuring the validation of four tires is confirmed.
Conclusion
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.
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/CHRISTOPHER W CARTER/Examiner, Art Unit 2117
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