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 .
Continued Examination Under 37 CFR 1.114
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 5/21/2026 has been entered.
Response to Amendment
Claims 1, 3, 8, 10, 15, 17, 22-23, 25, 27-28, 30, and 32-34 are amended, claims 2, 4-7, 9, 11-14, 16, 18-20, 24, and 29 are cancelled, and claims 35-36 are new. Claims 1, 3, 8, 10, 15, 17, 21-23, 25-28, and 30-36 are pending.
Response to Arguments
Applicant's arguments filed 5/21/2026 have been fully considered.
Regarding the objections to claims 1, 8, 15, 23-24, 28-29, and 33-34, and as noted on page 11 of the response, the amendments overcome the objections, which are withdrawn.
Regarding the rejections of independent claims 1, 8, and 15 under 101 as being directed to a judicial exception without significantly more, Examiner respectfully disagrees with Applicant’s arguments on pages 11-13 of the response for the following reasons.
On page 11 of the response, Applicant contends that the invention provides an improvement in computer-related technology as well as an improvement to at least the field of safety in industrial machinery by leveraging digital twin technology in improving the ability of asset management systems to identify assets requiring maintenance by understanding the data from tracking a loss in capacity, capabilities, and/or other functionalities which may enable the system to project required maintenance periods. In support, Applicant cites description in the specification regarding improvements in the ability to stagger maintenance and the ability of a user to monitor reduction in capability/capacities/functionalities of asserted by maintaining multiple digital twins in a library. In further support, Applicant notes on pages 12-13 that the independent claims are amended to incorporate these features including storing the digital twin “in a digital twin library,” “wherein the original state digital twin is a digital representation of each of the one or more assets when new, include at least original capabilities, capacities, and functionalities,” “wherein the maintenance is delayed or staggered for one or more specific assets to complete the activity based on an estimated time required for the maintenance determined utilizing a historical learning analysis of the digital twin library” and “displaying, to the user on an end-user device, the task management plan including the staggered maintenance schedule, wherein the staggered maintenance schedule includes a maintenance timeline for each asset of the one or more combinations of assets.”
Examiner submits that the utility (arguable improvement to the field of asset monitoring and maintenance planning) of the recited claims is largely confined to steps for implementing the digital twins and processing results (comparison) of the digital twins, and these steps fall within the judicial exception as set forth in the grounds for rejecting the independent claims. Examiner is unable to ascertain an improved aspect of asset monitoring and maintenance planning technology when considering individual elements and combinations of the elements including the “additional elements.” The thrust of the proposed invention appears to be identifying asset health/degradation via by comparing original (new) state performance with current state performance as supported by digital twins (data constructs) and machine learning model, which falls within the judicial exception, and the additional elements appear to constitute extra solution activity that fails to result in a combined improvement in asset monitoring/maintenance planning technology. Furthermore, considering each of the independent claims as a whole, the claim elements do not appear to convey an improved manner of processing the data and therefore do not embody an improvement to computer technology.
On page 12 of the response, Applicant cites significant amendments to dependent claims 3, 10, 17, 22-23, 25, 27-28, 30, and 32-36 in relation to eligibility under 101. As set forth with specificity in the current grounds of rejection, the dependent claims do not appear to include additional elements that when considered in combination with the elements of the independent claims do not result in the judicial exception being integrated into a practical application or in the claim as a whole amounting to significantly more than the judicial exception.
Regarding the rejections of independent claims 1, 8, and 15 under 103, Examiner agrees that the amendments overcome the rejections because none of Song, Hausler, and Deodhar appear to teach “wherein the maintenance is delayed or staggered for one or more specific assets to complete the activity based on an estimated time required for the maintenance determined utilizing a historical learning analysis of the digital twin library.” Therefore, the rejections of claims 1, 8, and 15 under 103 are withdrawn. However, Examiner notes that newly added element “wherein the maintenance is delayed or staggered for one or more specific assets to complete the activity based on an estimated time required for the maintenance determined utilizing a historical learning analysis of the digital twin library” does not appear to be disclosed with reasonable clarity as an embodiment of the disclosed invention by Applicant’s original disclosure and therefore claims 1, 8, and 15 and all claims depending therefrom are rejected under 112(a) as set forth below.
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.
Claims 1, 3, 8, 10, 15, 17, 21-23, 25-28, and 30-36 are rejected under 35 U.S.C. 112(a) as failing to comply with the written description requirement. 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, at the time the application was filed, had possession of the claimed invention.
Claim 1 lines 20-22 recites “wherein the maintenance is delayed or staggered for one or more specific assets to complete the activity based on an estimated time required for the maintenance determined utilizing a historical learning analysis of the digital twin library,” which does not appear to be disclosed with reasonable clarity by Applicant’s original disclosure as being part of the disclosed invention.
Applicant’s specification discloses delaying/staggering maintenance to complete an activity ([0045] maintenance may be delayed and/or productivity maintained resulting from simulations of differences in performance of original state digital twin and current state digital twin; [0052] maintenance delayed for an asset with completing an activity; [0054] delay maintenance for one or more assets to achieve an activity; [0017] and [0053] stagger maintenance of one or more assets to maintain productivity). Applicant’s specification further discloses an estimated time required for the maintenance that is determined utilizing a historical learning analysis of the digital twin library ([0046] digital twin library utilized in estimating time required for maintenance of assets based on historical learning). Paragraph [0050] disclosed determining an estimated time required for asset maintenance to increase capabilities, capacity, and safety differences. Paragraph [0052] further discloses estimated time required for asset maintenance as one of a list of possible components of a task management plan.
Applicant’s original disclosure does not appear to disclose, with reasonable clarity, the recited relation between the estimated time required for the maintenance and the delaying or staggering of maintenance for an asset to complete the activity. Namely, Applicant’s original disclosure does not appear to disclose “wherein the maintenance is delayed or staggered for one or more specific assets to complete the activity based on an estimated time required for the maintenance determined utilizing a historical learning analysis of the digital twin library,” with reasonable clarity.
Independent claims 8 and 15 include substantially the same elements as claim 1 that are not adequately supported by Applicant’s original disclosure and are therefore likewise rejected for the same reasons.
Claims 3, 21-23, 25, and 35-36 depending from claim 1, claims 10, 26-28, and 30 depending from claim 8, and claims 17 and 31-34 depending from claim 15 are likewise rejected for the same reasons as for their respective independent 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, 3, 8, 10, 15, 17, 21-23, 25-28, and 30-36 are rejected under 35 U.S.C. 101 because the claimed invention in each of these claims is directed to the abstract idea judicial exception without significantly more.
Independent claim 8, substantially representative also of claims 1 and 15, recites:
“[a] computer system for maintenance management, comprising:
one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories, wherein the computer system is capable of performing a method comprising:
receiving data for one or more assets of a physical ecosystem;
generating a digital twin of the physical ecosystem, wherein the digital twin of the physical ecosystem is stored in a digital twin library and includes at least an original state digital twin and a current state digital twin for each of the one or more assets of the physical ecosystem, wherein the original state digital twin is a digital representation of each of the one or more assets when new, include at least original capabilities, capacities, and functionalities;
simulating, utilizing one or more machine learning models, a performance of an activity identified by the user using the digital twin of the physical ecosystem including the original state digital twin and the current state digital twin for each of the one or more assets, wherein the one or more machine learning models leverage one or more simulation methods to compare an original state performance with a current state performance for each of the one or more assets;
identifying reduced capabilities, reduced capacities, and safety differences for each of the one or more assets based on a comparison of the original state performance with the current state performance for each of the one or more assets;
generating a task management plan based on the performance of the digital twin, wherein the task management plan includes one or more combinations of assets capable of performing the activity identified by the user and a staggered maintenance schedule for each of the one or more assets based on the reduced capabilities, the reduced capacities, and the safety differences, wherein the maintenance is delayed or staggered for one or more specific assets to complete the activity based on an estimated time required for the maintenance determined utilizing a historical learning analysis of the digital twin library; and
displaying, to the user on an end-user device, the task management plan including the staggered maintenance schedule, wherein the staggered maintenance schedule includes a maintenance timeline for each asset of the one or more combinations of assets.”
The claim limitations considered to fall within in the abstract idea are highlighted in bold font above and the remaining features are “additional elements.”
Step 1 of the subject matter eligibility analysis entails determining whether the claimed subject matter falls within one of the four statutory categories of patentable subject matter identified by 35 U.S.C. 101: process, machine, manufacture, or composition of matter. Claim 8 recites a system (apparatus/machine), claim 1 recites a method, and claim 15 recites an article of manufacture and each therefore falls within a statutory category.
Step 2A, Prong One of the analysis entails determining whether the claim recites a judicial exception such as an abstract idea. Under a broadest reasonable interpretation, the highlighted portions of claim 8 fall within the abstract idea judicial exception. Specifically, under the 2019 Revised Patent Subject matter Eligibility Guidance, the highlighted subject matter falls within the mental processes category (including an observation, evaluation, judgment, opinion) and the mathematical concepts category (mathematical relationships, mathematical formulas or equations, mathematical calculations). MPEP § 2106.04(a)(2).
The recited functions:
“receiving data for one or more assets of a physical ecosystem”
“leverage one or more simulation methods to compare an original state performance with a current state performance for each of the one or more assets”
“identifying reduced capabilities, reduced capacities, and safety differences for each of the one or more assets based on a comparison of the original state performance with the current state performance for each of the one or more assets” and
“generating a task management plan based on the performance of the digital twin, wherein the task management plan includes one or more combinations of assets capable of performing the activity identified by the user and a staggered maintenance schedule for each of the one or more assets based on the reduced capabilities, the reduced capacities, and the safety differences, wherein the maintenance is delayed or staggered for one or more specific assets to complete the activity based on an estimated time required for the maintenance determined utilizing a historical learning analysis of the digital twin library”
may be performed as mental processes.
Receiving data for one or more assets of a physical ecosystem may be performed via mental processes (e.g., observation of data related to assets such as may be presented on a computer display). Leveraging one or more simulation methods to compare an original state performance with a current state performance for each of the one or more assets may also be performed via mental processes (e.g., comparative evaluation of simulation method data relating to performance over time). Identifying reduced capabilities, reduced capacities, and safety differences for each of the one or more assets based on the comparison of the original state performance with the current state performance for each of the one or more assets may be performed via mental processes (e.g., evaluation of results of comparison results and judgement in determining/inferring corresponding asset conditions). Generating a task management plan based on performance of a digital twin, wherein the task management plan includes one or more combinations of assets capable of performing the activity identified by the user and a staggered maintenance schedule for each the one or more assets based on the reduced capabilities, the reduced capacities, and the safety differences, wherein the maintenance is delayed or staggered for one or more specific assets to complete the activity based on an estimated time required for the maintenance determined utilizing a historical learning analysis of the digital twin library may be performed via mental processes (e.g., evaluation of digital twin performance data and judgement in formulating/generating a task management plan that includes details such as combination of activity-capable assets and staggering of maintenance scheduling to account for compromised (reduced capability and safety) assets.
The recited functions “generating a digital twin of the physical ecosystem, wherein the digital twin of the physical ecosystem” “includes at least an original state digital twin and a current state digital twin for each of the one or more assets of the physical ecosystem, wherein the original state digital twin is a digital representation of each of the one or more assets when new, include at least original capabilities, capacities, and functionalities” and “simulating” “a performance of the digital twin of the physical ecosystem including the original state digital twin and the current state digital twin for each of the one or more assets” are determined by the Examiner as falling within the mathematical relationships sub-category of mathematical concepts (MPEP 2106.04(a)(2)) because, as is generally known and as disclosed by Applicant’s specification such as in paragraph [0048]) generating a digital twin and simulating performance of/by a digital twin are fundamentally characterized by mathematical relations and calculations (e.g., machine learning models for digital twin are mathematical constructs such as Convolutional Neural Networks (CNNs), Artificial Neural Network (ANN), Support Vector Machine (SVM), Monte Carlo simulation, other processing entailing statistical processing) and therefore constitute mathematical relationships.
Step 2A, Prong Two of the analysis entails determining whether the claim includes additional elements that integrate the recited judicial exception into a practical application. “A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception” (MPEP § 2106.04(d)).
MPEP § 2106.04(d) sets forth considerations to be applied in Step 2A, Prong Two for determining whether or not a claim integrates a judicial exception into a practical application. Based on the individual and collective limitations of claim 8 and applying a broadest reasonable interpretation, the most applicable of such considerations appear to include: improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)); applying the judicial exception with, or by use of, a particular machine (MPEP 2106.05(b)); and effecting a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)).
Regarding improvements to the functioning of a computer or other technology, none of the “additional elements” including a “computer system,” including “one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage medium, and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories,” the digital twin being “stored in a digital twin library,” using “one or more machine learning models” for performing steps including “simulating” and “leverage,” and “displaying, to the user on an end-user device, the task management plan including the staggered maintenance schedule, wherein the staggered maintenance schedule includes a maintenance timeline for each asset of the one or more combinations of assets” individually and in combination with the other claim elements, appear to integrate the judicial exception in a manner that technologically improves any aspect of a device or system that may be used to implement the highlighted steps or a device for implementing the highlighted steps such as a signal processing device or a generic computer. Instead, receiving data for the assets represents high level data collection and therefore extra solution activity. Using processor for implementing underlying function and storing a digital twin in a digital twin library (broadest reasonable interpretation of which entails essentially any accessible data storage) characterize well-known data processing components configured for implementing the underlying elements falling within the judicial exception and therefore constitutes insignificant extra solution activity that neither integrates the judicial exception into a practical application nor results in the claim as a whole amounting to significantly more than the judicial exception. Use of machine learning models represents using established types of programs/instructions for implementing the functions falling within the judicial exception and therefore constitutes insignificant extra solution activity that neither integrates the judicial exception into a practical application nor results in the claim as a whole amounting to significantly more than the judicial exception. Displaying, to the user on an end-user device, the task management plan including the staggered maintenance schedule, wherein the staggered maintenance schedule includes a maintenance timeline for each asset of the one or more combinations of assets represents outputting of the data processed in accordance with the steps falling within the judicial exception in which the displaying/outputting has no apparent particularized functional relation to the judicial exception and therefore also constitutes insignificant extra solution activity.
Regarding application of the judicial exception with, or by use of, a particular machine, the additional elements are not configured or implemented a particularized manner of implementing monitoring and maintenance management of a physical system.
Regarding a transformation or reduction of a particular article to a different state or thing, claim 8 does not include any such transformation or reduction. Instead, claim 8 as a whole entails receiving input information (data for assets of a physical ecosystem), applying standard processing components/ functions (computer processing using processors and memory and executing program instructions (e.g., machine learning)) to the information to determine simulation performance information with the additional elements failing to provide a meaningful integration of the abstract idea (digital twin simulation and task management plan determination/generation) in an application that transforms an article to a different state. Instead, the additional elements represent extra-solution activity that does not integrate the judicial exception into a practical application.
In view of the various considerations encompassed by the Step 2A, Prong Two analysis, claim 8 does not include additional elements that integrate the recited abstract idea into a practical application.
Therefore, claim 8 is directed to a judicial exception and requires further analysis under Step 2B.
Regarding Step 2B, and as explained in the Step 2A Prong Two analysis, the additional elements constitute insignificant extra solution activity and therefore in addition to failing to integrate the judicial exception into a practical application also fail to result in the claim as a whole amounting to significantly more than the judicial exception. Furthermore, most of the additional elements in claim 8 appear to be generic and well understood as evidenced by the disclosures of Song (US 2016/0247129 A1) and Hausler (US 2023/0214787 A1), each of which teach a substantially similar computing platform for implementing maintenance planning for a physical system.
Song teaches a “computer system (FIG. 3 data center 310; FIG. 11 computer system 1110, [0063]),” including “one or more processors (FIG. 11 processors 1120, [0064]), one or more computer-readable memories (FIG. 11 system memory 1130, [0065]), one or more computer-readable tangible storage medium (FIG. 11 system memory 1130 including ROM 1131 and RAM 1132, [0065]), and program instructions stored on at least one of the one or more tangible storage medium for execution by at least one of the one or more processors via at least one of the one or more memories (FIG. 11 operating system 1134 and application programs 1135 within RAM 1132)” as does Hausler ([0067]-[0068] describing implementation of the method via computer program. Examiner notes that computer program execution inherently requires a computer system having a processing and storage/memory for execution of instructions). Song further teaches accessible storage that may be used to store a digital twin (FIG. 11 system memory 1130 including ROM 1131 and RAM 1132, [0065]) and a display for maintenance planning output information (FIG. 3 depicting facility manager or operator 340 monitoring “HMI (dashboard)” interface to determine whether to “assign job” potentially for “maintenance” in accordance with modeling/simulation, [0037] required maintenance information may be observed by operator 340), as does Kamath (US 2022/0397888 A1) (FIG. 1B apparatus includes display 160 and GUI 165 accessible by personnel, [0039]; [0050] notifications may relate to maintenance). Hausler and Kamath each teach that machine learning may be utilized in conjunction with digital twin system analysis (Hausler: [0029] and [0085]. Kamath: [0010])).
Regarding “receiving data for one or more assets of a physical ecosystem,” the Examiner notes that even if this element is interpreted more narrowly such as to exclude mental processes (e.g., observation of displayed data), this element represents high level data gathering and hence constitute insignificant extra solution activity that neither integrates the judicial exception into a practical application (Step 2A Prong Two) nor results in the claim as a whole amounting to significantly more than the judicial exception (Step 2B).
Similarly, and regarding “generating a digital twin of the physical ecosystem, wherein the digital twin of the physical ecosystem” “includes at least an original state digital twin and a current state digital twin for each of the one or more assets of the physical ecosystem, wherein the original state digital twin is a digital representation of each of the one or more assets when new, including at least original capabilities, capacities, and functionalities” and “simulating” “a performance of the digital twin of the physical ecosystem including the original state digital twin and the current state digital twin for each of the one or more assets,” even if these elements individually and/or in combination are interpreted such that they do not fall within the mathematical concepts judicial exception, these elements essentially recite provisioning of and/or execution of computer instructions and data using well-known data processing functions (digital twinning) to implement the underlying element falling within the mental processes judicial exception (generating plan based on digital twin performance and ascertaining simulated performance based on asset data) and therefore constitute insignificant extra solution activity that neither integrates the judicial exception into a practical application (Step 2A Prong Two) nor results in the claim as a whole amounting to significantly more than the judicial exception (Step 2B).
For the foregoing reasons, the additional elements are insufficient to amount to significantly more than the judicial exception.
Independent claim 8 is therefore not patent eligible.
Independent claims 1 and 15 include substantially the same elements falling within the judicial exception as claim 8 and include no additional elements that integrate the abstract idea into practical application (Step 2A, Prong Two) or result in the claim amounting to “significantly more” test under the step 2B for the similar reasons as discussed with regards to claim 8.
Therefore claims 1 and 15 also constitute ineligible subject matter under 101.
Claims 3 and 21-23, 25, and 35-36 depending from claim 1, claims 10 and 26-28, and 30 depending from claim 8, and claims 17 and 31-34 depending from claim 15 provide additional features/steps that are part of an expanded algorithm that includes the abstract idea of the respective independent claim (Step 2A, Prong One). None of dependent claims 3, 10, 17, and 21-23, 25-28, and 30-36 recite additional elements that integrate the abstract idea into practical application (Step 2A, Prong Two), and all fail the “significantly more” test under the step 2B for similar reasons as discussed with regards to the independent claims.
For example, claim 3, substantially representative also of claims 10 and 17, recites “updating the current state digital twin stored in the digital twin library for each of the one or more assets of the physical ecosystem utilizing additional data, wherein the one or more assets include industrial machinery, and wherein the additional data is received in real time from a plurality of Internet of Things (IoT) devices associated with the physical ecosystem and one or more IoT devices associated with the industrial machinery,” which represents conventional, routine data processing activity (updating models using high level data collection) that constitutes extra solution that neither integrates the judicial exception into a practical application nor results in the claim as a whole amounting to significantly more than the judicial exception.
Claim 21, substantially representative also of claims 26 and 31 is an extension of the “simulating of the performance of the activity” step in claim 1 and therefore falls within the same mathematical concepts judicial exception, or as noted in the grounds for rejecting claim 8, if interpreted to fall outside the mathematical concepts exception, represents program implementation of a processing that may be performed via mental processes (ascertaining simulated performance based on asset data) such that it would constitute insignificant extra solution activity.
Claim 22, substantially representative also of claims 27 and 32, further characterizes the “reduced capacities” results of the comparing step in claims 1, 8, and 15 and therefore falls within the same mental processes judicial exception.
Claim 23, substantially representative also of claims 28 and 33, further recites “wherein the one or more combinations of assets capable of performing the activity are identified using based on historical data corresponding to the activity,” which may be performed via mental processes (e.g., evaluation of historical activity data to identify assets involved).
Claim 25, substantially representative also of claims 30 and 34, recites “wherein the staggered maintenance schedule is transmitted to the user utilizing one or more notifications or alerts on the end-user device,” which represents routine, conventional computer processing activity (outputting results of processing computations on a user display and transmitting output results using notifications/alert) having no particularized functional relation to the steps falling within the judicial exception, and therefore constitutes extra solution activity that neither integrates the judicial exception into a practical application nor results in the claim as a whole amounting to significantly more than the judicial exception.
Claim 35 recites that safety differences, which per claim 1 and reiterated in claim 35 are determined based on a comparison of original state and current state, are determined based on “monitoring of parameters, wherein the parameters include clearance and rotation angles for each of the one or more assets.” This further characterization of the digital twin related data does not appear to integrate the judicial exception into a practical application or result in the claim as a whole amounting to significantly more than the judicial exception because there is no apparent particularized functional relation between the nature of the input data (or how it is collected) and the steps falling within the judicial exception (e.g., the manner of comparison and/or determination of the “current state” and/or “original state” does not appear related to the nature of the data as comprising clearance and rotation angles).
Claim 36 further characterizes the combination of assets as meeting safety requirements based on a corresponding current state digital twin, which appears to recite an intended result of the invention rather than positively reciting an additional functional/structural limitation of the recited method, such that claim 36 is found to include no further additional elements that either integrate the judicial exception into a practical application or results in the claim as a whole amounting to significantly more than the judicial exception.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATTHEW W BACA whose telephone number is (571)272-2507. The examiner can normally be reached Monday - Friday 8:00 am - 5:30 pm.
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/MATTHEW W. BACA/Examiner, Art Unit 2857
/LINA CORDERO/Primary Examiner, Art Unit 2857
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