DETAILED ACTION
Claims 1, 3, 5, 7, 10, 12, 14, 16 and 19-20 are pending. Claims 2, 4, 6, 8-9, 11, 13, 15 and 17-18 are cancelled.
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 .
Priority
Acknowledgement is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d) to Indian Application No. 201921042436, filed on 10/18/2019.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 10/27/2025 has been entered.
Response to Arguments
Applicant’s arguments, filed 10/7/25, have been fully considered but are not persuasive, except where noted below.
Applicant’s arguments regarding the claim objection (page 14) is persuasive and this objection is withdrawn.
Applicant’s arguments regarding the rejections under 35 U.S.C. § 112 (pages 14-16) are persuasive and the claims are no longer rejected on these grounds. However, note that new grounds of rejection under 35 U.S.C. § 112(b) and 35 U.S.C. § 101 are presented below.
For at least these reasons, the rejection of the claims is maintained.
Claim Objections
The claims are objected to because of the following informalities:
‘as soon as they occur or as the system indicate a tendency towards the failure’ should read ‘as soon as they occur or as the system indicates a tendency towards the failure’ [claim 1].
‘as soon as they occur or as the system indicate a tendency towards the failure’ should read ‘as soon as they occur or as the system indicates a tendency towards the failure’ [claim 10].
‘as soon as they occur or as the system indicate a tendency towards the failure’ should read ‘as soon as they occur or as the system indicates a tendency towards the failure’ [claim 19].
Appropriate correction is required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(B) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim(s) 1, 3, 5, 7, 10, 12, 14, 16 and 19-20 is/are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Specifically, claim 1 recites ‘and cause and failure mode graph for passing detections from the process ontology to the root cause uniquely and identification of a duplicate knowledge’ and the meaning of this phrase is unclear. Also the failure mode graph lacks antecedent basis.
In addition, claim 1 recites ‘wherein the process ontology of a power generation industrial process in a thermal power plant and the power generation industrial process includes a sub-process including a coal combustion steam generation’ and the precise meaning of this limitation is unclear. It appears to suggest that the process ontology is associated with a power generation industrial process in a thermal power plant.
Claims 10 and 19 recite similar language to claim 1 and are rejected under the same rationale.
The dependent claims are also rejected under 35 U.S.C. § 112 as they inherit all of the characteristics of the claim from which they depend and none of the dependent claims provide a cure for the indefiniteness of the parent 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.
Claim(s) 1, 3, 5, 7, 10, 12, 14, 16 and 19-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claims do not fall within at least one of the four categories of patent eligible subject matter because the claimed invention is directed to an abstract idea, i.e. a mental process involving transforming abstract data, detecting a root cause by analyzing data, generating an abstract root cause path and pseudo codes and recommending actions based on the root cause analysis and related data.
Claim 1 recites a processor implemented method for real-time root cause analysis, i.e. a process, which is a statutory category of invention.
The claim recites the following:
transforming the root cause knowledge to a set of machine instructions, the set of machine instructions comprising an associated detection state of one or more detections identified through a detection model using data captured in real time by one or more sensors within the one or more equipment, wherein the associated detection state is at least one of a positive detection state and a negative detection state, wherein information from the one or more sensors is mapped to the process ontology, and wherein transforming the root cause knowledge to the set of machine instructions comprises deriving a logic in the set of machine instructions from the root cause knowledge by obtaining a pseudo code of the one or more detections along with the associated detection state;
generating… a root cause path comprising one or more root causes and associated interdependencies using (i) the process ontology and (ii) the transformed root cause knowledge, and wherein the one or more root causes are detected using the detection model, each root cause being connected to at least one other root cause and each root cause having the one or more detections;
generating… , a root cause graph using the root cause path, and wherein the root cause graph represents the one or more detections, root cause associated with each of the one or more detections, and detection state associated with each of the one or more detections, wherein the one or more root causes are detected using a binary detection based on a unique combination of the one or more detections and the associated detection state, through the detection model,
wherein the root cause graph comprises a performance indicator (PI) that is used as a trigger for performing root cause analysis in real-time, wherein a first root cause comprised in the root cause graph is indicative of the performance indicator (PI) corresponding to the one or more industrial processes, wherein one or more root causes are hierarchical arranged after the first root cause in the root cause graph in a plurality of levels, and wherein root causes of a level of the plurality of levels are directly affected by deviation in root causes of a previous level of the plurality of levels, wherein the root cause graph is a visual representation of the root cause along with the industrial process and equipment knowledge, and wherein the root cause graph is created by combining knowledge from the process ontology, and cause and failure mode graph for passing detections from the process ontology to the root cause uniquely and identification of a duplicate knowledge;
performing…, root cause analysis, in real time, using the root cause graph after converting the root cause graph into pseudo codes, wherein the root cause graph enables identification of at least one of a redundant knowledge and a conflicting knowledge of each root cause associated with each of the one or more detections, wherein if a same set of detections and their corresponding detection states are connected with more than one root cause, then a case of the redundant knowledge is identified, and if two different set of detections and their corresponding detection states are connected to a same root cause, then a case of the conflicting knowledge is identified, wherein the root cause analysis is triggered based on the redundant knowledge and the conflicting knowledge of each root cause when one of a failure occurs in a system or a subsystem of the industry plant, and when the system or the subsystem in the industry plant is indicating a possible failure, and
wherein a pseudo code of the pseudo codes is a textual representation of unit knowledge of a root cause or a root cause path, wherein the root cause analysis in real-time requires knowledge of the root cause for the industrial process in a computer implementable format and real-time detection of failures as soon as they occur or as the system indicate a tendency towards the failure through information coming from the one or more sensors; and
recommending,… one or more actions to be executed for rectifying each root cause in the root cause graph based on the root cause analysis, deviation in the performance indicator (PI), and the arrangement of root causes in the plurality of levels that may be performed in the human mind, or by a human using a pen and paper. Thus the claim recites an abstract idea (mental process), see MPEP 2106.04(a).
This judicial exception is not integrated into a practical application because the additional elements, i.e. implementing the method with a generic hardware processor (applying the exception with a generic computer, see MPEP 2106.04(a)(2) III C), an industrial process (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), and obtaining, via one or more hardware processors, information pertaining to one or more industrial processes being executed by one or more equipment in an industry plant, wherein the information comprises piping and instrumentation diagram (PID), operational data, maintenance history, root cause knowledge, and a process model, and wherein the root cause knowledge is based on the PID, the operational data, the maintenance history, and the process model, wherein the information represents knowledge of the one or more equipment, a failure mode and the root cause analysis; receiving, via the one or more hardware processors, a process ontology and wherein the process ontology comprises information pertaining to one or more of (i) the one or more equipment, (ii) a location of one or more sensors deployed within the one or more equipment, (iii) sensory information captured through the one or more sensors thereof, wherein the one or more sensors measure one or more parameters including a velocity estimated by a velocity sensor, a quality estimated by a quality estimation sensor, a pressure or force estimated by a pressure sensor or a force sensor, a temperature estimated by a temperature sensor, a density estimated by a density sensor, corresponding to performance of the one or more equipment, (iv) information on an interaction between at least one of (a) the one or more equipment and (b) the one or more industrial processes, (v) one or more parameters of the one or more industrial processes, or (vi) one or more action plans, and wherein the one or more action plans comprise one or more of repair, mitigation, containment, or control of at least one of the one or more industrial processes and the one or more equipment (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 A, 2106.05(d) and 2106.05(g)), and wherein the process ontology of a power generation industrial process in a thermal power plant and the power generation industrial process includes a sub-process including a coal combustion steam generation, wherein the power generation industrial process has a process parameter including a load and during operation of the thermal power plant, the thermal power plant generates the load through the power generation industrial process and the power generation industrial process starts with coal combustion through the sub-process producing gas as an output, wherein the thermal power plant comprises the one or more equipment including a boiler, a turbine, a generator, wherein the boiler further comprises equipment part including a super heater, a water wall, wherein the water wall further comprises a sub-equipment including a soot blower (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), do not impose any meaningful limits on practicing the abstract idea. The claim is therefore directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, implementing the method with a generic hardware processor (applying the exception with a generic computer, see MPEP 2106.04(a)(2) III C), an industrial process (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), and obtaining, via one or more hardware processors, information pertaining to one or more industrial processes being executed by one or more equipment in an industry plant, wherein the information comprises piping and instrumentation diagram (PID), operational data, maintenance history, root cause knowledge, and a process model, and wherein the root cause knowledge is based on the PID, the operational data, the maintenance history, and the process model, wherein the information represents knowledge of the one or more equipment, a failure mode and the root cause analysis; receiving, via the one or more hardware processors, a process ontology and wherein the process ontology comprises information pertaining to one or more of (i) the one or more equipment, (ii) a location of one or more sensors deployed within the one or more equipment, (iii) sensory information captured through the one or more sensors thereof, wherein the one or more sensors measure one or more parameters including a velocity estimated by a velocity sensor, a quality estimated by a quality estimation sensor, a pressure or force estimated by a pressure sensor or a force sensor, a temperature estimated by a temperature sensor, a density estimated by a density sensor, corresponding to performance of the one or more equipment, (iv) information on an interaction between at least one of (a) the one or more equipment and (b) the one or more industrial processes, (v) one or more parameters of the one or more industrial processes, or (vi) one or more action plans, and wherein the one or more action plans comprise one or more of repair, mitigation, containment, or control of at least one of the one or more industrial processes and the one or more equipment (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 A, 2106.05(d) and 2106.05(g)), and wherein the process ontology of a power generation industrial process in a thermal power plant and the power generation industrial process includes a sub-process including a coal combustion steam generation, wherein the power generation industrial process has a process parameter including a load and during operation of the thermal power plant, the thermal power plant generates the load through the power generation industrial process and the power generation industrial process starts with coal combustion through the sub-process producing gas as an output, wherein the thermal power plant comprises the one or more equipment including a boiler, a turbine, a generator, wherein the boiler further comprises equipment part including a super heater, a water wall, wherein the water wall further comprises a sub-equipment including a soot blower (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)) is not considered significantly more. Considering the additionally elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea.
Note that industrial plants with sensors are well-understood, routine and conventional, see Wu et al. U.S. Patent Publication No. 20060117295 [0003], Hirooka et al. U.S. Patent Publication No. 20200201285 [0003] and the other prior art previously cited. Also note that power plants with coal combustion through the sub-process producing gas as an output, wherein the thermal power plant comprises the one or more equipment including a boiler, a turbine, a generator, wherein the boiler further comprises equipment part including a super heater, a water wall, wherein the water wall further comprises a sub-equipment including a soot blower are well-understood, routine and conventional, see for example Best U.S. Patent No. 2097268 (pages 2-4), Thayer et al. U.S. Patent No. 3163154 (particularly cols. 3-4), Abeyta U.S. Patent Publication Nos. 20110132282, 20120247405 and 20150086930 (particularly 0004-0009, 0066-0068, 0105) and the English translation of Yamanaka Japanese Patent Document No. 3809981, published 2006 (particularly 0013-0018).
Claim 3 recites various types of abstract model. Thus this claim recites an abstract idea.
Claim 5 recites various types of abstract model. Thus this claim recites an abstract idea.
Claim 7 recites details of the abstract root graph, e.g. a tree format. Thus this claim recites an abstract idea.
Claim 10 recites a system, i.e. a machine, which is a statutory category of invention. The claim recites the following:
transform the root cause knowledge to a set of machine instructions, the set of machine instructions comprising an associated detection state of one or more detections identified through a detection model using data captured in real time by one or more sensors within the one or more equipment,
wherein the associated detection state is at least one of a positive detection state and a negative detection state, wherein information from the one or more sensors is mapped to the process ontology,
wherein transforming the root cause knowledge to the set of machine instructions comprises deriving a logic in the set of machine instructions from the root cause knowledge by obtaining a pseudo code of the one or more detections along with the associated detection state;
generate a root cause path comprising one or more root causes and associated interdependencies using (i) the process ontology and (ii) the transformed root cause knowledge, and
wherein the one or more root causes are detected using the detection model, each root cause being connected to at least one other root cause and each root cause having the one or more detections;
generate a root cause graph using the root cause path, wherein the root cause graph represents the one or more detections, root cause associated with each of the one or more detections, and detection state associated with each of the one or more detections,
wherein the one or more root causes are detected using a binary detection based on a unique combination of the one or more detections and the associated detection state, through the detection model,
wherein the root cause graph comprises a performance indicator(PI) that is used as a trigger for performing root cause analysis in real-time,
wherein a first root cause comprised in the root cause graph is indicative of the performance indicator (PI) corresponding to the one or more industrial processes, wherein one or more root causes are hierarchical arranged after the first root cause in the root cause graph in a plurality of levels, wherein root causes of a level of the plurality of levels are directly affected by deviation in root causes of a previous level of the plurality of levels,
wherein the root cause graph is a visual representation of the root cause along with the industrial process and equipment knowledge, and wherein the root cause graph is created by combining knowledge from the process ontology, and
cause and failure mode graph for passing detections from the process ontology to the root cause uniquely and identification of a duplicate knowledge;
perform root cause analysis, in real time, using the root cause graph after converting the root cause graph into pseudo codes, wherein the root cause graph enables identification of at least one of a redundant knowledge and a conflicting knowledge of each root cause associated with each of the one or more detections,
wherein if a same set of detections and their corresponding detection states are connected with more than one root cause, then a case of the redundant knowledge is identified, and if two different set of detections and their corresponding detection states are connected to a same root cause, then a case of the conflicting knowledge is identified,
wherein the root cause analysis is triggered based on the redundant knowledge and the conflicting knowledge of each root cause when one of a failure occurs in a system or a subsystem of the industry plant, and when the system or the subsystem in the industry plant is indicating a possible failure,
wherein a pseudo code of the pseudo codes is a textual representation of unit knowledge of a root cause or a root cause path,
wherein the root cause analysis in real-time requires knowledge of the root cause for the industrial process in a computer implementable format and real-time detection of failures as soon as they occur or as the system indicate a tendency towards the failure through information coming from the one or more sensors; and
recommend one or more actions to be executed for rectifying each root cause in the root cause graph based on the root cause analysis, deviation in the performance indicator (PI), and the arrangement of root causes in the plurality of levels that may be performed in the human mind, or by a human using a pen and paper. Thus the claim recites an abstract idea (mental process), see MPEP 2106.04(a).
This judicial exception is not integrated into a practical application because the additional elements, i.e. a memory storing instructions; one or more communication interfaces; and one or more hardware processors coupled to the memory via the one or more communication interfaces (applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C, MPEP 2106.05(d) II and MPEP 2106.05(g)), an industrial plant (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), and obtain information pertaining to one or more industrial processes being executed by one or more equipment in an industry plant, wherein the information comprises piping and instrumentation diagram (PID), operational data, maintenance history, root cause knowledge, and a process model, and wherein the root cause knowledge is based on the PID, the operational data, the maintenance history, and the process model, wherein the information represents knowledge of the one or more equipment, a failure mode and the root cause analysis; receive a process ontology, and wherein the process ontology comprises information pertaining to one or more of (i) the one or more equipment, (ii) a location of one or more sensors deployed within the one or more equipment, (iii) sensory information captured through the one or more sensors thereof, wherein the one or more sensors measure one or more parameters including a velocity estimated by a velocity sensor, a quality estimated by a quality estimation sensor, a pressure or force estimated by a pressure sensor or a force sensor, a temperature estimated by a temperature sensor, a density estimated by a density sensor, corresponding to performance of the one or more equipment, (iv) information on an interaction between at least one of (a) the one or more equipment and (b) the one or more industrial processes, (v) one or more parameters of the one or more industrial processes, or (vi) one or more action plans, and wherein the one or more action plans comprise one or more of repair, mitigation, containment, or control of at least one of the one or more industrial processes and the one or more equipment (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 A, 2106.05(d) and 2106.05(g)) and the power generation industrial process has a process parameter including a load and during operation of the thermal power plant, the thermal power plant generates the load through the power generation industrial process and the power generation industrial process starts with coal combustion through the sub-process producing gas as an output, wherein the thermal power plant comprises the one or more equipment including a boiler, a turbine, a generator, wherein the boiler further comprises equipment part including a super heater, a water wall, wherein the water wall further comprises a sub-equipment including a soot blower (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)) do not impose any meaningful limits on practicing the abstract idea. The claim is therefore directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, a memory storing instructions; one or more communication interfaces; and one or more hardware processors coupled to the memory via the one or more communication interfaces (applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C, MPEP 2106.05(d) II and MPEP 2106.05(g)), an industrial plant (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), and obtain information pertaining to one or more industrial processes being executed by one or more equipment in an industry plant, wherein the information comprises piping and instrumentation diagram (PID), operational data, maintenance history, root cause knowledge, and a process model, and wherein the root cause knowledge is based on the PID, the operational data, the maintenance history, and the process model, wherein the information represents knowledge of the one or more equipment, a failure mode and the root cause analysis; receive a process ontology, and wherein the process ontology comprises information pertaining to one or more of (i) the one or more equipment, (ii) a location of one or more sensors deployed within the one or more equipment, (iii) sensory information captured through the one or more sensors thereof, wherein the one or more sensors measure one or more parameters including a velocity estimated by a velocity sensor, a quality estimated by a quality estimation sensor, a pressure or force estimated by a pressure sensor or a force sensor, a temperature estimated by a temperature sensor, a density estimated by a density sensor, corresponding to performance of the one or more equipment, (iv) information on an interaction between at least one of (a) the one or more equipment and (b) the one or more industrial processes, (v) one or more parameters of the one or more industrial processes, or (vi) one or more action plans, and wherein the one or more action plans comprise one or more of repair, mitigation, containment, or control of at least one of the one or more industrial processes and the one or more equipment (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 A, 2106.05(d) and 2106.05(g)) and the power generation industrial process has a process parameter including a load and during operation of the thermal power plant, the thermal power plant generates the load through the power generation industrial process and the power generation industrial process starts with coal combustion through the sub-process producing gas as an output, wherein the thermal power plant comprises the one or more equipment including a boiler, a turbine, a generator, wherein the boiler further comprises equipment part including a super heater, a water wall, wherein the water wall further comprises a sub-equipment including a soot blower (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)) is not considered significantly more. Considering the additionally elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea.
Claims 12, 14 and 16 recite similar limitations to claims 3, 5 and 7 and are rejected under the same respective rationales.
Claim 19 recites one or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause a method for real-time root cause analysis, i.e. an article of manufacture, which is a statutory category of invention.
The claim recites the following:
transforming the root cause knowledge to a set of machine instructions, the set of machine instructions comprising an associated detection state of one or more detections identified through a detection model using data captured in real time by one or more sensors within the one or more equipment, wherein the associated detection state is at least one of a positive detection state and a negative detection state, wherein information from the one or more sensors is mapped to the process ontology, and wherein transforming the root cause knowledge to the set of machine instructions comprises deriving a logic in the set of machine instructions from the root cause knowledge by obtaining a pseudo code of the one or more detections along with the associated detection state;
generating a root cause path comprising one or more root causes and associated interdependencies using (i) the process ontology and (ii) the transformed root cause knowledge, and wherein the one or more root causes are detected using the detection model, each root cause being connected to at least one other root cause and each root cause having the one or more detections;
generating a root cause graph using the root cause path, wherein the root cause graph represents the one or more detections, root cause associated with each of the one or more detections, and detection state associated with each of the one or more detections,
wherein the one or more root causes are detected using a binary detection based on a unique combination of the one or more detections and the associated detection state, through the detection model, wherein the root cause graph comprises a performance indicator (PI) that is used as a trigger for performing root cause analysis in real-time,
wherein a first root cause comprised in the root cause graph is indicative of the performance indicator (PI) corresponding to the one or more industrial processes,
wherein one or more root causes are hierarchical arranged after the first root cause in the root cause graph in a plurality of levels,
wherein root causes of a level of the plurality of levels are directly affected by deviation in root causes of a previous level of the plurality of levels,
wherein the root cause graph is a visual representation of the root cause along with the industrial process and equipment knowledge, and wherein the root cause graph is created by combining knowledge from the process ontology, and cause and failure mode graph for passing detections from the process ontology to the root cause uniquely and identification of a duplicate knowledge; and
performing root cause analysis, in real time, using the root cause graph after converting the root cause graph into pseudo codes, wherein the root cause graph enables identification of at least one of a redundant knowledge and a conflicting knowledge of each root cause associated with each of the one or more detections, wherein if a same set of detections and their corresponding detection states are connected with more than one root cause, then a case of the redundant knowledge is identified, and if two different set of detections and their corresponding detection states are connected to a same root cause, then a case of the conflicting knowledge is identified, wherein the root cause analysis is triggered based on the redundant knowledge and the conflicting knowledge of each root cause when one of a failure occurs in a system or a subsystem of the industry plant, and when the system or the subsystem in the industry plant is indicating a possible failure,
wherein a pseudo code of the pseudo codes is a textual representation of unit knowledge of a root cause or a root cause path, wherein the root cause analysis in real-time requires knowledge of the root cause for the industrial process in a computer implementable format and real-time detection of failures as soon as they occur or as the system indicate a tendency towards the failure through information coming from the one or more sensors; and
recommending one or more actions to be executed for rectifying each root cause in the root cause graph based on the root cause analysis, deviation in the performance indicator (PI), and the arrangement of root causes in the plurality of levels that may be performed in the human mind, or by a human using a pen and paper. Thus the claim recites an abstract idea (mental process), see MPEP 2106.04(a).
This judicial exception is not integrated into a practical application because the additional elements, i.e. non-transitory machine-readable information storage mediums comprising one or more instructions executed by one or more hardware processors (applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C, MPEP 2106.05(d) II and MPEP 2106.05(g)), an industrial plant (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), and obtaining information pertaining to one or more industrial processes being executed by one or more equipment in an industry plant, wherein the information comprises piping and instrumentation diagram (PID), operational data, maintenance history, root cause knowledge, and a process model, and wherein the root cause knowledge is based on the PID, the operational data, the maintenance history, and the process model, wherein the information represents knowledge of the one or more equipment, a failure mode and the root cause analysis; receiving a process ontology, and wherein the process ontology comprises information pertaining to one or more of (i) the one or more equipment, (ii) a location of one or more sensors deployed within the one or more equipment, (iii) sensory information captured through the one or more sensors thereof, wherein the one or more sensors measure one or more parameters including a velocity estimated by a velocity sensor, a quality estimated by a quality estimation sensor, a pressure or force estimated by a pressure sensor or a force sensor, a temperature estimated by a temperature sensor, a density estimated by a density sensor, corresponding to performance of the one or more equipment, (iv) information on an interaction between at least one of (a) the one or more equipment and (b) the one or more industrial processes, (v) one or more parameters of the one or more industrial processes, or (vi) one or more action plans, and wherein the one or more action plans comprise one or more of repair, mitigation, containment, or control of at least one of the one or more industrial processes and the one or more equipment (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 A, 2106.05(d) and 2106.05(g)) and the process ontology of a power generation industrial process in a thermal power plant and the power generation industrial process includes a sub-process including a coal combustion steam generation, wherein the power generation industrial process has a process parameter including a load and during operation of the thermal power plant, the thermal power plant generates the load through the power generation industrial process and the power generation industrial process starts with coal combustion through the sub-process producing gas as an output, wherein the thermal power plant comprises the one or more equipment including a boiler, a turbine, a generator, wherein the boiler further comprises equipment part including a super heater, a water wall, wherein the water wall further comprises a sub-equipment including a soot blower (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)) do not impose any meaningful limits on practicing the abstract idea. The claim is therefore directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, non-transitory machine-readable information storage mediums comprising one or more instructions executed by one or more hardware processors (applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C, MPEP 2106.05(d) II and MPEP 2106.05(g)), an industrial plant (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), and obtaining information pertaining to one or more industrial processes being executed by one or more equipment in an industry plant, wherein the information comprises piping and instrumentation diagram (PID), operational data, maintenance history, root cause knowledge, and a process model, and wherein the root cause knowledge is based on the PID, the operational data, the maintenance history, and the process model, wherein the information represents knowledge of the one or more equipment, a failure mode and the root cause analysis; receiving a process ontology, and wherein the process ontology comprises information pertaining to one or more of (i) the one or more equipment, (ii) a location of one or more sensors deployed within the one or more equipment, (iii) sensory information captured through the one or more sensors thereof, wherein the one or more sensors measure one or more parameters including a velocity estimated by a velocity sensor, a quality estimated by a quality estimation sensor, a pressure or force estimated by a pressure sensor or a force sensor, a temperature estimated by a temperature sensor, a density estimated by a density sensor, corresponding to performance of the one or more equipment, (iv) information on an interaction between at least one of (a) the one or more equipment and (b) the one or more industrial processes, (v) one or more parameters of the one or more industrial processes, or (vi) one or more action plans, and wherein the one or more action plans comprise one or more of repair, mitigation, containment, or control of at least one of the one or more industrial processes and the one or more equipment (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 A, 2106.05(d) and 2106.05(g)) and the process ontology of a power generation industrial process in a thermal power plant and the power generation industrial process includes a sub-process including a coal combustion steam generation, wherein the power generation industrial process has a process parameter including a load and during operation of the thermal power plant, the thermal power plant generates the load through the power generation industrial process and the power generation industrial process starts with coal combustion through the sub-process producing gas as an output, wherein the thermal power plant comprises the one or more equipment including a boiler, a turbine, a generator, wherein the boiler further comprises equipment part including a super heater, a water wall, wherein the water wall further comprises a sub-equipment including a soot blower (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)) is not considered significantly more. Considering the additionally elements individually and in combination and the claim as a whole, the additional elements do not provide significantly more than the abstract idea.
Claim 20 recites various types of abstract process model (similar to claim 3) and various types of abstract detection model (similar to claim 5). Thus this claim recites an abstract idea.
Citation of Pertinent Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Cheng et al. U.S. Patent Publication No. 20060191896 discloses a system for analyzing the impact of operating soot blowers in a heat transfer section of a coal power plant.
Note that any citations to specific, pages, columns, lines, or figures in the prior art references and any interpretation of the reference should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. See MPEP 2123.
Conclusion
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/BERNARD G LINDSAY/
Primary Examiner, Art Unit 2119