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 .
Claim Status
Claims 1-20 are pending. The pending claims comprise 3 groups:
1) System1: 1-10, and
2) Method1: 11-18, and
3) Product1: 19-20.
All appear to have similar scope.
As of 02/28/2024, method claim 1 is broader and will be examined first.
11. A method, comprising:
[1] monitoring, by a system comprising a processor, industrial asset data generated by industrial assets that are in service within an industrial facility, wherein the industrial asset data comprises operational and status information for the industrial assets;
[2] determining, by the system based on analysis of the industrial asset data, whether a subset of the industrial asset data satisfies a condition indicative of a current or predicted risk to an industrial asset of the industrial assets; and
in response to determining that the subset of the industrial asset data satisfies the condition, [3] determining, by the system, one or more maintenance tasks predicted to mitigate the current or predicted risk; and
[4] generating, by the system, a work order prescribing the one or more maintenance tasks,
wherein the determining of the one or more maintenance tasks comprises [5] generating a prompt, directed to a generative artificial intelligence (AI) model, designed to cause the generative AI model to generate a response that is processed to determine the one or more maintenance tasks.
Note: for referential purpose, numerals [1]-[4] are added to the beginning of each steps.
1. A system, comprising:
[I] a memory that stores executable components and work order data defining closed work orders for maintenance tasks that have been completed; and
[II] a processor, operatively coupled to the memory, that executes the executable components, the executable components comprising:
[III] a monitoring component configured to monitor industrial asset data generated by industrial assets in service within an industrial facility, wherein the industrial asset data comprises operational and status information for the industrial assets;
[IV] an analysis component configured to determine, based on analysis of the industrial asset data, whether a subset of the industrial asset data satisfies a condition indicative of a current or predicted risk to an industrial asset of the industrial assets, and
in response to determining that the subset of the industrial asset data satisfies the condition, formulate one or more maintenance tasks predicted to mitigate the current or predicted risk; and
[V] a work order generation component configured to, in response to the determination by the analysis component that the subset of the industrial data satisfies the condition,
[1] generate a work order prescribing the one or more maintenance tasks, wherein the analysis component is configured to, as part of the analysis,
[2] generate a prompt, directed to a generative artificial intelligence (AI) model, designed to obtain a response from the generative AI model that is used by the analysis component to at least one of determine whether the subset of the industrial asset data satisfies the condition or formulate the one or more maintenance tasks.
Note: for referential purpose, numerals [I]-[V] and [1]-[2] are added to the beginning of each step.
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 to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step 1: when considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e.,
(1) process,
(2) machine,
(3) manufacture or product, or
(4) composition of matter.
Step 2A, Prong 1: If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception, i.e.,
1) law of nature,
2) natural phenomenon, and
3) abstract idea.
and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception. If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself. Examples of abstract ideas include:
(1) Mathematical concepts -- mathematical relationships, mathematical formulas or equations, and mathematical calculations;
(2) Mental processes—concepts performed in the human mind (including an observation, evaluation, judgment, and opinion).
(3) Certain methods of organizing human activities.
(i) fundamental economic principles or practices (including hedging, insurance, mitigating risk);
(ii) commercial or legal interactions (including agreements in the form of contracts; Legal obligations; Advertising, marketing or sales activities or behaviors; business relations);
(iii) managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
For instance, in Alice Corp. (Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 134 S. Ct. 2347 (2014)), the Court found that “intermediated settlement” was a fundamental economic practice, which is considered as (1) a certain method of organizing human activities, which is an abstract idea.
Step 1:
In the instant case, with respect to claims 1-20:
Claim categories:
2) Method1: 11-18, and
1) System1: 1-10.
3) Product: 19-20.
Analysis of Step 1:
Method: claims 11-18 are directed to method for generating a maintenance work order of an industrial asset comprising the steps for monitoring the asset by collecting operation data about the asset, analyzing the data, if the operation condition exceeds a risk level, determining a maintenance task to mitigate the risk, and generating a work order includes a maintenance task to reduce the risk level, wherein the determining step includes a query/response exchange with a generative AI model. (Step 1:Yes).
2. System1: claims 1-10 are directed to a system, comprising a memory, a processor, executes the executable components, a monitoring component, an analysis component, and work order components, to carry out a maintenance work order generation of an industrial asset by collecting operation data about the asset, analyzing the data, if the operation condition exceeds a risk level, determining a maintenance task to mitigate the risk, and generating a work order includes a maintenance task to reduce the risk level, wherein the determining step includes a query/response exchange to a generative AI model. (Step 1: Yes).
Product: claims 19-20 are directed to product for carrying out a method for generating a maintenance work order of an industrial asset comprising the steps for monitoring the asset by collecting operation data about the asset, analyzing the data, if the operation condition exceeds a risk level, determining a maintenance task to mitigate the risk, and generating a work order includes a maintenance task to reduce the risk level, wherein the determining step includes a query/response exchange with a generative AI model. (Step 1:Yes).
Thus, the claims 1-20 are generally directed towards one of the four statutory categories under 35 USC § 101.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A,
(1) Prong One: Does the claim recite a judicial exception?
(2) Prong Two: Are there any additional elements that integrate the judicial exception into a practical application?
Only if a claim (1) recites a judicial exception and (2) does not integrate that exception into a practical application, then proceeds to step 2B.
Step 2B: Are there any additional elements that adds an inventive concept to the claim? Determine whether the claim:
(3) adds a specific limitation beyond the judicial exception that is not “well-understood, routine, and conventional” in the field (see MPEP 2106.05(d)); or
(4) simply appends well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception.
A. Step 2A, Prong One:
Claim 1, as exemplary, recites a system/method for generating a maintenance work order, is a fundamental economic principle or business practice for generating a work order for preventive maintenance of an industrial asset, which is considered as (i) a certain method of organizing human activities, which is an abstract idea.
(ii) commercial or legal interactions (including agreements in the form of contracts; Legal obligations; Advertising, marketing or sales activities or behaviors; business relations);
Furthermore, independent claims 1, 11 and 19 recite an abstract idea related to evaluation/analyzing an asset conditions by collecting operation data, analyzing the data to determine if a risk condition exist, if the condition exceeds a threshold value, determine a maintenance task to reduce the risk, then generate a work order including the task, wherein the task determining step includes a query/response exchange with a generative AI model, which constitutes an abstract idea based on “Mental Processes” related to concepts performed in the human mind including observation, evaluation, judgment, and opinion.
(2) Mental processes—concepts performed in the human mind (including an observation, evaluation, judgment, and opinion).
B. Step 2A, Prong Two:
The judicial exception is not integrated into a practical applications because it deals with a method for generating a maintenance work order of an industrial asset, by carrying out steps of:
The claims recites the additional elements of:
Steps: Types
[1] Monitor (collect)… asset data. Data gathering, insignificant extra-solution activity (IE-SA) step.
[2] determine …condition of asset. Mental/analysis/comparing values.
* Query/response with AI model. Mental/analysis/recommendation.
[3] generate … work order (data). Mental/business activity/data displaying, IE-SA.
Step [1] and [3] are data gathering and outputting data which are considered as insignificant extra-solution activity steps.
Step [2] is for evaluating/analyzing the collected data about the asset conditions and determine a preventive maintenance task to restore the condition of the asset back to normal and then generating a work order containing the task. These mental steps are well known business activities for monitoring and managing an asset.
The claim does not result in an improvement to the functioning of the computer system or to any other technology or technical field. Further, the claim limitations are not indicative of integration into a practical application by applying or using the judicial exception in some other meaningful way. The combination of the additional elements, a computer, monitoring component, analysis component, work order generation component, and generative AI model, no more than mere instructions to apply the exception using a generic devices. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea (e.g., a fundamental economic practice or mental processes) for generating a maintenance work order of an industrial asset based on the monitoring conditions and does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
C. Step 2B:
The claims recites the additional elements of steps [1]-[3] above.
Step [1] and [3] are data gathering and outputting data which are considered as insignificant extra-solution activity steps.
Step [2] is for evaluating/analyzing the collected data about the asset conditions and determine a preventive maintenance task to restore the condition of the asset back to normal and then generating a work order containing the task. These mental steps are well known business activities for monitoring and managing an asset.
The claim does not result in an improvement to the functioning of the computer system or to any other technology or technical field. Further, the claim limitations are not indicative of integration into a practical application by applying or using the judicial exception in some other meaningful way. The combination of the additional elements, a computer, monitoring component, analysis component, work order generation component, and generative AI model, no more than mere instructions to apply the exception using a generic devices. Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea (e.g., a fundamental economic practice or mental processes) for generating a maintenance work order of an industrial asset based on the monitoring conditions and does not integrate a judicial exception into a practical application. See MPEP 2106.05(f).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above, the additional elements, step [2] when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea(s). As for the system claims, mere instructions to apply an exertion using generic computer components cannot provide an inventive concept. These generic computer components, a computer, monitoring component, analysis component, work order generation component, and generative AI model, etc., are claimed at high level of generality to perform their basis functions which amount to no more than generally linking the use of the judicial exception to the particular technological environment of field of use and further see insignificant extra-solution activity MPEP 2106.05 (f), (g) and (h). The Symantec, TLI, and OIP Techs, court decisions cited in MPEP 2106.05(d)(II) indicate that mere receipt or transmission of data over a network, sorting data, analyzing data, and transmitting the data is a well-understood, routine and conventional function when it is claimed in a merely generic manner (as it is here). The claim are basically collect data, analyze data, and provide set of results, which are not patent eligible, see Electric Power Group, LLC. For these reasons, there is no inventive concept in the claim, and thus the claim is not patent eligible.
As for dep. claims 2-3 (part of 1 above), which deal with further details of the analysis value of the proposed task, these further limit the abstract idea of the analysis effectiveness, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claims 2-3 are not considered as being “significantly more”, and thus do not facilitate the claim to meet the “inventive concept”.
As for dep. claims 4 and 6 (part of 1 above), which deal with further details of the analysis components, these further limit the abstract idea of the analysis effectiveness, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claims 4 and 6 are not considered as being “significantly more”, and thus do not facilitate the claim to meet the “inventive concept”.
As for dep. claim 5 (part of 1 above), which deals with further details of the query/response communication with the AI model, this further limits the abstract idea of the analysis effectiveness, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claim 5 is not considered as being “significantly more”, and thus do not facilitate the claim to meet the “inventive concept”.
As for dep. claims 7-8 (part of 1 above), which deal with further details of the content analysis of the request, these further limit the abstract idea of the analysis effectiveness, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claims 7-8 are not considered as being “significantly more”, and thus do not facilitate the claim to meet the “inventive concept”.
As for dep. claims 9-10 (part of 1 above), which deal with further details of the created work order using a GUI, these further limit the abstract idea of the creation of the work order, without including: (a) an improvement to another technology or technical field, (b) an improvement to the functioning of the computer itself, or (c ) meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. Therefore, claims 9-10 are not considered as being “significantly more”, and thus do not facilitate the claim to meet the “inventive concept”.
Claims 11-18 are the method claims of the system claims 1-10 are rejected for the same reason set forth above. Claims 19-20 are the product claims of the method claims 11-18 and are rejected for the same reason set forth above.
Therefore, claims 1-20 are not drawn to eligible subject matter as they are directed to an abstract idea without significantly more. step 2B: NO
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
On October 10, 2007, the Patent Office issued the "Examination Guidelines for Determining Obviousness Under 35 U.S.C. 103 in View of the Supreme Court Decision in KSR International Co. v. Teleflex Inc.," 73 Fed. Reg. 57,526 (2007) (hereinafter the Examination Guidelines). Section III is entitled "Rationales to support rejections under 35 U.S.C. 103." Within this section is the following quote from the Supreme Court: "rejections on obviousness grounds cannot be sustained by merely conclusory statements; instead there must be some articulated reasoning with some rational underpinning to support the legal conclusion of obviousness." KSR Int'l Co. v. Teleflex Inc., 127 S. Ct. 1727, 1741 (2007) (quoting In re Kahn, 441 F.3d 977, 988 (Fed. Cir. 2006)).
Under the Examination Guidelines, the following is a list of rationales that may be used to support a finding of obviousness under 35 U.S.C. § 103:
(a) combining prior art elements according to known methods to yield predictable results;
(b) simple substitution of one known element for another to obtain predictable results;
(c) Use of known technique to improve similar devices (methods, or products) in the same way;
(d) Applying a known technique to a known device (method, or product) ready for improvement to yield predictable results;
(e) "Obvious to try" choosing from a finite number of identified, predictable solutions, with a reasonable expectation of success;
(f) Known work in one field of endeavor may prompt variations of it for use in either the same field or a different one based on design incentives or other market forces if the variations would have been predictable to one of ordinary skill in the art; and
(g) Some teaching, suggestion, or motivation (TSM) in the prior art that would have led one of ordinary skill to modify the prior art reference or to combine prior art reference teachings to arrive at the claimed invention.
Each rationale is resolved using the Graham factual inquiries.
Claims 11, 14-18 (method1), and respective 1, 4-8 and 10 (system1) and respective 19-20 (article1) are rejected under 35 U.S.C. 103(a) as obvious over:
Names Publications:
(1) ZHOU ET AL. US 2021/0.302.953, and
(2) NAGESHWAR ET AL. US 2024/0.362.257.
As for independent claim 11, ZHOU ET AL. discloses a method, comprising:
[1] monitoring, by a system comprising a processor, industrial asset data generated by industrial assets that are in service within an industrial facility, wherein the industrial asset data comprises operational and status information for the industrial assets;
{see [0017 … preventive maintenance system uses live data from sensors related to the operation of the systems monitored ….],
Fig. 3, 310 “Analyze data, 311 “Process Raw data,”, 350,“Maintenance order Management,” 350.
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[0019 … specific monitored systems (e.g. pumps, wells, filter),…] The pumps/wells read over industrial assets that are in service within an industrial facility.
The “live data” normally includes “operational and status information” of the asset.
[0032..data binning (313) to group or cluster data point having similar ranges of values into “bins” to simplify or reduce … data points into data set for analysis…]}
[2] determining, by the system based on analysis of the industrial asset data, whether a subset of the industrial asset data satisfies a condition indicative of a current or predicted risk to an industrial asset of the industrial assets; and
{see [0017 … live data from sensors related to the operation of the systems monitored for preventive maintenance…. Root cause analysis, …, more accurate prediction model for the failure or nonconformances…]
[0035 …analyses includes generating alerts (341) when the incoming data exceed various identified threshold in operation rule sets… operational status … that are monitored for preventive maintenance]}
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[0037…a case of population of systems for analysis … to identify targeted non-conformings (per blocks 412)]
in response to determining that the subset of the industrial asset data satisfies the condition, [3] determining, by the system, one or more maintenance tasks predicted to mitigate the current or predicted risk; and
{see [0018.. the work orders provide explanations of the problems, what resources were needed to resolve the problems, what labor was required to resolve the problems,…”]}
[4] generating, by the system, a work order prescribing the one or more maintenance tasks,
{see Fig. 3, 350 “Maintenance order Management,” 351, “Generate work order,”
see [0018.. the work orders provide explanations of the problems, what resources were needed to resolve the problems, what labor was required to resolve the problems,…”]}
ZHOU ET AL. fairly teaches claim 11 except for explicitly discloses the determined maintenance task to mitigate risk comprises generating a prompt to an AI model and receiving a response from the AI model.
In a similar industrial facility, NAGESHWAR ET AL. discloses that a work order request for determining maintenance task to reduce risk (error) may comprise generating a prompt to a Large Language Models (LLG) (or Machine learning (ML) or Artificial Intelligence (AI)) and receiving a response from the AI model wherein the response provides additional information about how to handle the problem or task identified in the work order, see [0026] and [0028], and Fig. 4A and 4B.
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[0034 … The enterprise interpretation model …. Maintenance, technical support…]
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Therefore, it would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to modify the asset monitoring system of ZHOU ET AL. by including an electronic communications with a generative artificial intelligence (AI) model as taught by NAGESHWAR ET AL. for additional information about how to handle the problem or task identified in the work order, see Fig. 4B, and [0028].
As for independent system claim 1, the processor is cited in ZHOU ET AL. Fig. 9, Computing device 900, the monitoring component is shown in Fig. 3, element 300, the analysis component is shown in 310, 340, the work order generation component is shown in 351, part of 350 “Maintenance order Management.”
As for the independent non-transitory computer readable medium (CRM) claim 19, this is shown in ZHOU ET AL. Fig. 9, 960.
As for dep. claim 14 (part of 11 above) and respective 4 (part of 1 above), which deals with subset of data set used in the training data of the model for determining the type of maintenance task, i.e. information from past work orders, this is taught in ZHOU ET AL. [0037 …training data into a model generator 404…], [0017 preventive maintenance system uses … historical work order information for previous non-conformances in the system and related systems…providing the more accurate prediction model for the failure or nonconformances.], and [0038]
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As for dep. claim 15 (part of 11 above) and respective 5 (part of 1 above), which deals with set of data submitted in the “generating of the prompt” to the Generative AI Model, comprising of a selected data subset, this is taught in ZHOU ET AL. / NAGESHWAR ET AL. in view of ZHOU ET AL. Fig. 3, and [0032 … cluster of data point having similar ranges of values … for analysis].
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As for dep. claim 16 (part of 11 above) and respective 6 (part of 1 above), which deals with the learning of the system for further analysis, this is taught in ZHOU ET AL. [0038-0039]
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As for dep. claim 17 (part of 11 above) and respective 7 (part of 1 above), which deals with rendering a content of the work order features, this is taught in ZHOU Fig. 3, 351, “Generate Work Order,” Fig. 8, 840, “Create a Work Order,”, 820 “Display Alerts, etc. The display of work order with a description of a maintenance task would have been obvious in view of the teaching of “displaying Alerts” of the analysis. Alternatively, this is taught in NAGESHWAR ET AL. Fig. 4A “P0/P1 Work orders.”
Dependent claim(s) 12-13 (part of 11 above) and respective 2-3 (part of 1 above) are rejected under 35 U.S.C. 103 as being unpatentable over ZHOU ET AL. / NAGESHWAR ET AL. as applied to claims 11 and 1 above, and further in view of (3) LIU ET AL., US 2020/0.167.263.
As for dep. claim 12 (part of 11 above), and respective 2 (part of 1 above) and respective 20 (part of 19 above), which deal with a score of the effectiveness of the proposed maintenance task, wherein the score represents the degree of compliance with respect to a grading metrics, this is fairly taught in ZHOU ET AL. [0046]
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Note that ZHOU ET AL. teaches the combined score (624) is generated from the combination of the (1) Productivity impact factor 623, (2) Inventory factor 622 , and (3) Prediction quality factor 621. The selection of other factors such as compliance factor would have been obvious as mere selection of other performance effectiveness.
ZHOU / NAGESHWAR ET AL. does not teach the feature of a score less than a defined threshold.
LIU ET AL. is cited to teach the step of in response to determining that a score, is less than a defined threshold score, changing the input (content of the message) and affecting the score.
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Therefore, it would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to modify the asset monitoring system of ZHOU ET AL./ NAGESHWAR ET AL. by including the step of in response to determining that a score, is less than a defined threshold score, changing the input (content of the message) as taught by LIU ET AL. for managing the input.
As for dep. claim 13 (part of 11 above) and respective 3 (part of 1 above), which deals with a score of the effectiveness of the proposed maintenance task and a grading metrics of the maintenance task, this is taught in ZHOU ET AL. [0046] wherein the proposed maintenance task is related to the asset quality factor, or inventory factor, or productivity impact factor or maintenance length, impact of the predicted maintenance, etc. The selection of other factors affecting the asset for carrying out the task such as compliance or safety factor would have been obvious as mere selection of other impact asset factors.
Claim(s) 9 is rejected under 35 U.S.C. 103 as being unpatentable over ZHOU ET AL. / NAGESHWAR ET AL. as applied to claims 1, 3-8 above, and further in view of (4) NAPOLI, US 2018/0.225.795.
NAPOLI ET AL. teaches the rendering a list of work orders as a ranked list according relative priorities using a GUI component, Fig. 2, and [0025].
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Therefore, it would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to modify the asset monitoring system of ZHOU ET AL./ NAGESHWAR ET AL. by rendering a list of work orders as a ranked list according relative priorities using a GUI component as taught by NAPOLI for effective workflow task management, see abstract.
Claim(s) 18 (part of 11 above) and 8 and 10 (part of 1 above) are rejected under 35 U.S.C. 103 as being unpatentable over ZHOU ET AL. / NAGESHWAR ET AL. as applied to claims 11, 13-17 and 1, 3-7 above, and further in view of (5) HATTANGADY ET AL., USP 11,962,546.
As for dep. claim 18 (part of 11 above) and respective 10 (part of 1 above), the teachings of ZHOU /NAGESHWAR ET AL. are cited above.
HATTANGADY ET AL., on col. 1, lines 5-15, teaches the use of productivity application such as Generative AI Model for converting task into projects with schedules or scheduled activities for solving a problem. The inclusion of well known scheduling parameters such as on a recurring basis would have been obvious if the problem occurs on a recurring basis.
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Therefore, it would have been obvious to a person having ordinary skill in the art (PHOSITA) before the effective filing date of the claimed invention to modify the asset monitoring system of ZHOU ET AL./ NAGESHWAR ET AL. by including the use of productivity application such as Generative AI Model for converting task into projects with schedules or scheduled activities for solving a problem as taught by HATTANGADY ET AL. for improving productivity. The inclusion of well known scheduling parameters such as on a recurring basis would have been obvious if the problem occurs on a recurring basis.
As for claim 8 which deals with the feature of a GUI to render a chat session configured to receive a natural language request/query directed to the work order, this is taught in HATTANGADY ET AL. Fig. 3A or 3G.
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The use of natural language request or query to the work order is taught in ZHOU [0003] and it would have been obvious to apply this feature in the GUI of HATTANGADY ET AL. in the received request/query or work order.
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Citations of Pertinent Prior Art
1) US 2016/0.155.098 by McElhinney discloses a Historical Health Metrics system for preventive maintenance system.
No claims are allowed.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Tan "Dean" D NGUYEN whose telephone number is (571)272-6806. The examiner can normally be reached on M-F: 6:30-4:30 PM (ET).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sarah M Monfeldt can be reached on 571-270-1833. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/TAN D NGUYEN/Primary Examiner, Art Unit 3689
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