DETAILED ACTION
Claims 1-13 and 15-20 are pending. Claims 14 and 21 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 German Patent Application No. 102022108584.8 filed on 4/8/2022.
Response to Arguments
Applicant’s arguments, filed 1/7/26, have been fully considered but are not persuasive.
Applicant argues that the claims do not fall into the category of ‘a mental process’ because ‘The subject matter defined in amended claim 1 and 11 clearly constitutes a technical solution to a technical problem, and is not merely a task performable in the human mind. The claim relates to a method for automatically determining a current state of a technical system during its real operation. For this purpose, multiple types of process-relevant data are acquired, each of which is directly linked to physical processes in the system: disturbances of the ongoing process, real process times of individual process steps, and the actual consumption of media and electrical energy. These features each relate to concrete technical influencing variables that occur during system operation and are physically measurable. The claimed subject matter does not use these measured variables for an abstract data analysis or a purely mathematical evaluation, but rather subjects them to a process-integrated technical evaluation with the aim of reliably and automatically determining the operational state of the plant.
Thus, when acquiring disturbance data, for example, not merely an abstract error code is registered, but physical fault events of different technical effects are detected, which may manifest themselves in the real process as a plant stoppage, a temporal delay, or uninterrupted continued operation. These events have immediate technical consequences for plant operation, and their acquisition serves to derive the actual technical load state of the system.
Likewise, the acquired process times do not represent abstract time markers, but rather temporal characteristic values of specific technical sequences such as, for example, ramp-up, CIP, SIP, cooling, or production interruption. These sequences each concern concrete mechanical or fluid-technical processes within the plant. Recording these times allows conclusions to be drawn regarding system stability, process quality, and current process load, rather than regarding a purely mathematical pattern.
The acquisition of media and energy consumption is also not performed in the form of abstract numerical data, but is based on real physical measurement processes within the plant that are directly linked to the operation of technical components such as pumps, heating circuits, or drives. These quantities constitute an objective measure of system utilization, efficiency, and load and provide technically usable information about its condition.
The claim-required step of determining a process indicator number is thus based on technically deterministic input variables, all of which are based on real physical processes. In this context, the process indicator number does not represent a mathematical end in itself, but rather functions as a compressed technical condition indicator that is formed from immediately operation-specific parameters and that can serve as a basis for technical follow-up measures.
The formation of this key figure is not comparable to an abstract analysis or a mere data aggregation as typically encountered in the context of non-technical data evaluations, but is an integral part of an overall technical process that enables automatic condition assessment and process control of a real industrial system.
The core of the claimed subject matter therefore lies in combining physically detectable, process-specific, and technically relevant data into a technical key figure that represents the current condition of the plant and can form the basis for intervention-capable technical control decisions. The claimed subject matter thus does not relate to an abstract idea, but to a technical operational problem of real plants, namely the reliable, automated, and objectively robust determination of plant condition from multiple simultaneously occurring technical influencing factors.’ (pages 9-11).
It is respectfully submitted that determining a process indicator number based on gathered data is not a technical solution to a technical problem, and is merely a task performable in the human mind or by a human using pen and paper, e.g. humans are capable of adding or multiplying a series of numbers that are presented to them to arrive at a numerical result. The fact that the gathered data ‘relate to concrete technical influencing variables’ or ‘physical fault events’ does not make the gathered data non-abstract — the data remain abstract values. It is noted that actual ‘plant stoppage’ or actual physical ‘technical consequences for plant operation’, for example are not claimed. ‘pumps, heating circuits, or drives’ are moot as they are not actually claimed. That the process indicator ‘can serve as a basis for technical follow-up measure’ is merely an intended use for the abstract data and meaningful, non-generic, follow-up measures are not actually claimed. The fact that the gathered data are relevant to a plant is considered generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h) and not significantly more than the abstract idea. And that ‘technical key figure that represents the current condition of the plant and can form the basis for intervention-capable technical control decisions’ is an unclaimed intended use for the abstract result. It is also noted that merely determining a process indicator number alone does not result in improved operation of an actual plant. Applicant’s arguments are therefore not persuasive.
Applicant’s arguments relating to the rejection under 35 U.S.C. § 103 (pages 12-15) are moot in view of the new combination of references in the current rejection, including the newly cited reference, Kawai.
For at least these reasons, the rejection of the claims is maintained.
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) 1-13 and 15-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a 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 the abstract idea (mental process) of determining a process indicator number based on data.
Claim 1 recites a method for automatically determining a current condition of a system in operation, i.e. a process, which is a statutory category of invention. The claim recites:
determining a process indicator number based on the first data, the second data, and the third data 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 processes), see MPEP 2106.04(a).
This judicial exception is not integrated into a practical application because the additional elements, i.e. a system in operation (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), and acquiring first data relating to one or more faults in the system during a process; acquiring second data relating to a process time in the system during the process; acquiring third data relating to media and energy consumption in the system during the process, and during the acquisition of the third data, measuring a quantity of media or electrical energy used (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d)) do not impose any meaningful limits on practicing the abstract idea. The claim is therefore directed to an abstract idea.
Note that a system in operation and devices are well-understood, routine and conventional, see for example the references previously cited in the Non-Final Office Action and in the current rejection under 35 U.S.C. § 103 .
The claims do 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 system in operation (generally linking the use of the judicial exception to a particular technological environment or field of use, see MPEP 2106.05(h)), and acquiring first data relating to one or more faults in the system during a process; acquiring second data relating to a process time in the system during the process; acquiring third data relating to media and energy consumption in the system during the process, and during the acquisition of the third data, measuring a quantity of media or electrical energy used (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d)) are 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. Thus the claim is not patent eligible.
Claim 2 recites ‘using the determined process indicator number to determine whether to initiate at least one of maintenance, troubleshooting, cleaning, service, and repair work’ (mental process). Thus this claim recites an abstract idea.
Claim 3 recites ‘acquiring at least one of the following: first faults in the system which lead to a process stoppage of the process; second faults in the system which lead to an extension of the process in time; and third faults in the system that do not lead to any extension in time and to no process stoppage of the process’ (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d)). Thus this claim recites an abstract idea.
Claim 4 recites ‘classifying the first faults, the second faults, and the third faults into a respective first class, second class, and third class’ (mental process), ‘wherein different weighting is respectively used in the first class, the second class, and the third class, and wherein a maximum first weighting in the first, second, and third classes totals 50% of the process indicator number’ (abstract descriptive material). Thus this claim recites an abstract idea.
Claim 5 recites ‘acquiring: a process time of at least one of: a ramp-up of the system; a cleaning-in-place (CIP); a sterilization-in-place (SIP); a rinsing step; a cooling step; a production interruption; and a ramp-down of the system (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d)), wherein a maximum second weighting totals 30% of the process indicator number’ (abstract descriptive material). Thus this claim recites an abstract idea.
Claim 6 recites ‘wherein a maximum third weighting amounts to 20% of the process indicator number’ (abstract descriptive material). Thus this claim recites an abstract idea.
Claim 7 recites ‘storing at least one of: the process indicator number; and the first, second, and third data’ (applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C or mentally remembering data). Thus this claim recites an abstract idea.
Claim 8 recites ‘storing an operating state of the system’ (applying the exception with generic computer technology, see MPEP 2106.04(a)(2) III C or mentally remembering data). Thus this claim recites an abstract idea.
Claim 9 recites ‘analyzing the first faults, the second faults, and/or the third faults including: associating, during the analysis, events in the system that are related to one another in terms of time; and making, during the analysis, an association to environmental conditions of the system’ (mental process involving analyzing data). Thus this claim recites an abstract idea.
Claim 10 recites ‘creating a time profile of the process indicator number; and comparing the time profile of the process indicator number with a preceding time profile of the process indicator number’ (mental process performed by a human, or by a human using a pen and paper). Thus this claim recites an abstract idea.
Claim 11 recites a device for automatically determining a current condition of a system in operation, i.e. a machine, which is a statutory category of invention. However, the process performed by the generic device that the method is generally linked to (see MPEP 2106.05(h)) is similar to that recited in claim 1 and is rejected under the same rationale. Thus this claim recites an abstract idea.
Claim 12 recites the device is further configured to perform an acquisition function to acquire the first data, the second data, and/or the third data (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d)). Thus this claim recites an abstract idea.
Claim 13 recites the device is further configured to perform a determination function to determine the process indicator number based on the first data, the second data, and the third data, and/or to create a time profile of the process indicator number (mental process). Thus this claim recites an abstract idea.
Claim 15 recites ‘acquire at least one of the following: first faults in the system which lead to a process stoppage of the process; second faults in the system which lead to an extension of the process in time; and third faults in the system that do not lead to any extension in time and to no process stoppage of the process’ (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d)). Thus this claim recites an abstract idea.
Claim 16 recites ‘perform an analysis function for analyzing at least one of the first faults, the second faults, and the third faults’ (mental process involving analyzing data). Thus this claim recites an abstract idea.
Claim 17 recites ‘classify the first faults, the second faults, and the third faults into a respective first class, second class, and third class, wherein different weighting is respectively used in the first class, the second class, and the third class’ (mental process), and ‘wherein a maximum first weighting in the first, second, and third classes totals 50% of the process indicator number’ (abstract descriptive material). Thus this claim recites an abstract idea.
Claim 18 recites ‘classifying the first faults, the second faults, and the third faults into a respective first class, second class, and third class’ (mental process), and ‘wherein different weighting is respectively used in the first class, the second class, and the third class’ (abstract descriptive material). Thus this claim recites an abstract idea.
Claim 19 recites ‘a maximum weighting in the first, second, and third classes totals 50% of the process indicator number’ (abstract descriptive material). Thus this claim recites an abstract idea.
Claim 20 recites ‘acquiring a process time of at least one of: a ramp-up of the system; a cleaning-in-place (CIP); a sterilization-in-place (SIP); a rinsing step; a cooling step; a production interruption; and a ramp-down of the system’ (insignificant extra-solution elements – mere data gathering, see MPEP 2106.05 I A, MPEP 2106.05(g) MPEP 2106.05(d)), and ‘wherein a maximum weighting totals 30% of the process indicator number’ (abstract descriptive material). Thus this claim recites an abstract idea.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102 of this title, 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 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 7-8, and 11-13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kavaklioglu et al. U.S. Patent Publication No. 20070067142 (hereinafter Kavaklioglu) in view of Kawai U.S. Patent Publication No. 20140316602 (hereinafter Kawai).
Regarding claim 1, Kavaklioglu teaches a method for automatically determining a current condition of a system in operation [0011, Fig. 1 — system and method of monitoring an entity having a plurality of lower level entities, is described herein, which accounts for varying degrees of importance among the lower level entities. In one aspect, use indices pertaining to status information of the lower level entities is acquired. Further, weighting values are acquired. Generally, the weighing value pertains to the importance of a lower level entity among the plurality of lower level, such as the priority or criticality of the lower level entity; 0030, 0037-0038, Fig. 2 — asset utilization expert 50 may include or execute index generation software 51 that creates indices associated with devices, like process control and instrumentation devices, power generation devices, rotating equipment, units, areas, etc, or that are associated with process control entities, like loops, etc. within the plant 10. The asset utilization expert 50 may further include or execute an index aggregation routine 60. The index aggregation routine 60 utilizes indices generated by the index generation routine 51 or other index generation routines to create indices associated with various levels within a process control system (current condition of a system), or more generally an asset utilization system, which may include one or more process control systems. The index aggregation routine 60 further includes a weighting value when creating an aggregate index associated with a process, unit, area], the method comprising:
acquiring first data relating to one or more faults in the system during a process [0041-0045 —index aggregation routine 60 may acquire weighting values related to each device, loop, sub-unit, unit, area, plant, etc. within a group by receiving each weighting value from another source or by creating each weighting value based on information from a variety of sources. For example, the index aggregation routine 60 may receive data relating to the impact and frequency of failure of each device; 0066 — In the case of calculating a PI for a loop, the system may, for example, compare the maximum or average loop error (i.e., the steady state error signal) to some predetermined minimum error value which, ideally, may be zero. In this manner, a small loop error may correspond to a PI value that is indicative of good performance];
acquiring second data relating to a process time in the system during the process [0066 —FIG. 4 is an exemplary table that illustrates one manner in which the performance index (PI), the health index (HI), the variability index (VI) and the utilization index (UI) may or may not be generated for the device, loop, sub unit and unit levels of the system hierarchy; 0070 — the UI may be calculated for the loop, sub unit and unit levels, but may not necessarily be calculated for the device level. Generally speaking, the UI represents the degree to which a particular asset (e.g., a loop, a sub unit or a unit) is being exploited in comparison to its capacity or desired utilization. For example, the UI value may be based on the amount of time for which a unit, sub unit or loop is being used to perform control or produce outputs. Additionally or alternatively, the UI value may be based on the amount of material which is being processed by the loop];
acquiring third data relating to media consumption in the system during the process [0070 — the UI may be calculated for the loop, sub unit and unit levels, but may not necessarily be calculated for the device level….Additionally or alternatively, the UI value may be based on the amount of material which is being processed by the loop]; and
determining a process indicator number based on the first data, the second data, and the third data [0030, Fig. 2 — asset utilization expert 50 may include or execute index generation software 51 that creates indices associated with devices, like process control and instrumentation devices, power generation devices, rotating equipment, units, areas, etc, or that are associated with process control entities, like loops, etc. within the plant 10. The asset utilization expert 50 may further include or execute an index aggregation routine 60. The index aggregation routine 60 utilizes indices generated by the index generation routine 51 or other index generation routines to create indices associated with various levels within a process control system (current condition of a system), or more generally an asset utilization system, which may include one or more process control systems. The index aggregation routine 60 further includes a weighting value when creating an aggregate index associated with a process, unit, area; 0037-0038 — the index aggregation routine 60 receives information from various data sources, which may include data collectors, data generators or data tools including index generation routines 51… This information may include indices related to the health, performance, utilization and variability of a particular device, loop, unit, area, etc.; 0045-0051 — index aggregation routine 60 may calculate the aggregate index as a weighted average according to the following general equation… the aggregate index u is provided as a number from 0 to 100].
But Kavaklioglu fails to clearly specify acquiring data relating to energy consumption in the system during the process, and during the acquisition of the third data, measuring a quantity of media or electrical energy used.
However, Kawai teaches acquiring data relating to energy consumption in the system during the process, and during the acquisition of the third data, measuring a quantity of media or electrical energy used [0044-0046, Figs. 1-2 — Each of the wattmeters 11 through 14 is an integrating wattmeter measuring (informing) a total amount of electric energy consumed by a corresponding one of the machines A through D. Specifically, the wattmeter 11 measures a total amount of electric energy consumed by the machine A.].
Kavaklioglu and Kawai are analogous art. They relate to industrial control systems, particularly those including maintenance systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by Kavaklioglu, by incorporating measured electrical energy consumption in the process, as taught by Kawai.
One of ordinary skill in the art would have been motivated to do this modification in order to account for electrical energy consumption in a machine, for example to enable suppressing wasteful electric power consumption, as suggested by Kawai [0018-0021, 0082, 0091]. In addition, it would be obvious to one having ordinary skill in the art to simply substitute known electrically powered machines of Kawai for the generic device/assets of Kavaklioglu for the predictable result of a method for determining a condition of a system based on media and electrical energy consumption of electrical machines.
Regarding claim 7, the combination of Kavaklioglu and Kawai teaches all the limitations of the base claims as outlined above.
Further, Kavaklioglu teaches storing at least one of: the process indicator number; and the first, second, and third data [0038 — index aggregation routine 60 receives information from various data sources, which may include data collectors, data generators or data tools including index generation routines 51, model generation routines 56, control routines 62, maintenance system applications 64, data historians 66, diagnostic routines 68, etc.; 0043 — index aggregation routine 60 is communicatively coupled to model generation routines 56, control routines 62, maintenance system applications 64, data historians 66 (stored data), diagnostic routines 68, or other data sources as shown in FIG. 2. Each of the various types of information may be used to evaluate the impact and/or frequency of failure of an asset within a group of assets. For example, historical information, diagnostic information and maintenance information may provide information regarding previous failures of a device, while historical information, process information, on-line monitoring information and heuristic information may provide information on the impact of past failures on the group or the predicted impact of a failure on the group].
Regarding claim 8, the combination of Kavaklioglu and Kawai teaches all the limitations of the base claims as outlined above.
Further, Kavaklioglu teaches storing an operating state of the system [0068 — The manufacturer may program a device to provide an HI value which is indicative of the current status of the life cycle of the device… For example, a stroke type valve may have an expected useful operating life cycle of 250,000 full stroke cycles and the manufacturer of the stroke valve device, which is typically a smart field device, has stored in its memory the expected number of lifetime operating strokes along with the current number strokes that the valve has completed (operating state of the system)].
Regarding claim 11, Kavaklioglu teaches a device for automatically determining a current condition of a system in operation [0011, Fig. 1 — system and method of monitoring an entity having a plurality of lower level entities, is described herein, which accounts for varying degrees of importance among the lower level entities. In one aspect, use indices pertaining to status information of the lower level entities is acquired. Further, weighting values are acquired. Generally, the weighing value pertains to the importance of a lower level entity among the plurality of lower level, such as the priority or criticality of the lower level entity; 0030, 0037-0037-0038, Fig. 2 — index aggregation routine 60 may be centrally located at a particular server, which may be maintained locally at the plant 10 or remotely from the plant 10. Alternatively, the index aggregation routine 60 may be distributed among several computers such as business system computers 35, maintenance computers 18, 22, maintenance planning computers 36… asset utilization expert 50 may include or execute index generation software 51 that creates indices associated with devices, like process control and instrumentation devices, power generation devices, rotating equipment, units, areas, etc, or that are associated with process control entities, like loops, etc. within the plant 10. The asset utilization expert 50 may further include or execute an index aggregation routine 60. The index aggregation routine 60 utilizes indices generated by the index generation routine 51 or other index generation routines to create indices associated with various levels within a process control system (current condition of a system), or more generally an asset utilization system, which may include one or more process control systems. The index aggregation routine 60 further includes a weighting value when creating an aggregate index associated with a process, unit, area], t wherein the device is configured to:
acquire first data relating to one or more faults in the system during a process [0041-0045 —index aggregation routine 60 may acquire weighting values related to each device, loop, sub-unit, unit, area, plant, etc. within a group by receiving each weighting value from another source or by creating each weighting value based on information from a variety of sources. For example, the index aggregation routine 60 may receive data relating to the impact and frequency of failure of each device; 0066 — In the case of calculating a PI for a loop, the system may, for example, compare the maximum or average loop error (i.e., the steady state error signal) to some predetermined minimum error value which, ideally, may be zero. In this manner, a small loop error may correspond to a PI value that is indicative of good performance];
acquire second data relating to a process time in the system during the process [0066 —FIG. 4 is an exemplary table that illustrates one manner in which the performance index (PI), the health index (HI), the variability index (VI) and the utilization index (UI) may or may not be generated for the device, loop, sub unit and unit levels of the system hierarchy; 0070 — the UI may be calculated for the loop, sub unit and unit levels, but may not necessarily be calculated for the device level. Generally speaking, the UI represents the degree to which a particular asset (e.g., a loop, a sub unit or a unit) is being exploited in comparison to its capacity or desired utilization. For example, the UI value may be based on the amount of time for which a unit, sub unit or loop is being used to perform control or produce outputs. Additionally or alternatively, the UI value may be based on the amount of material which is being processed by the loop];
acquire third data relating to media consumption in the system during the process [0070 — the UI may be calculated for the loop, sub unit and unit levels, but may not necessarily be calculated for the device level….Additionally or alternatively, the UI value may be based on the amount of material which is being processed by the loop]; and
determine a process indicator number based on the first data, the second data, and the third data [0030, Fig. 2 — asset utilization expert 50 may include or execute index generation software 51 that creates indices associated with devices, like process control and instrumentation devices, power generation devices, rotating equipment, units, areas, etc, or that are associated with process control entities, like loops, etc. within the plant 10. The asset utilization expert 50 may further include or execute an index aggregation routine 60. The index aggregation routine 60 utilizes indices generated by the index generation routine 51 or other index generation routines to create indices associated with various levels within a process control system (current condition of a system), or more generally an asset utilization system, which may include one or more process control systems. The index aggregation routine 60 further includes a weighting value when creating an aggregate index associated with a process, unit, area; 0037-0038 — the index aggregation routine 60 receives information from various data sources, which may include data collectors, data generators or data tools including index generation routines 51… This information may include indices related to the health, performance, utilization and variability of a particular device, loop, unit, area, etc.; 0045-0051 — index aggregation routine 60 may calculate the aggregate index as a weighted average according to the following general equation… the aggregate index u is provided as a number from 0 to 100].
But Kavaklioglu fails to clearly specify acquiring data relating to energy consumption in the system during the process, and during the acquisition of the third data, measuring a quantity of media or electrical energy used.
However, Kawai teaches acquiring data relating to energy consumption in the system during the process, and during the acquisition of the third data, measuring a quantity of media or electrical energy used [0044-0046, Figs. 1-2 — Each of the wattmeters 11 through 14 is an integrating wattmeter measuring (informing) a total amount of electric energy consumed by a corresponding one of the machines A through D. Specifically, the wattmeter 11 measures a total amount of electric energy consumed by the machine A.].
Kavaklioglu and Kawai are analogous art. They relate to industrial control systems, particularly those including maintenance systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by Kavaklioglu, by incorporating measured electrical energy consumption in the process, as taught by Kawai.
One of ordinary skill in the art would have been motivated to do this modification in order to account for electrical energy consumption in a machine, for example to enable suppressing wasteful electric power consumption, as suggested by Kawai [0018-0021, 0082, 0091]. In addition, it would be obvious to one having ordinary skill in the art to simply substitute known electrically powered machines of Kawai for the generic device/assets of Kavaklioglu for the predictable result of a device for determining a condition of a system based on media and electrical energy consumption of electrical machines.
Regarding claim 12, the combination of Kavaklioglu and Kawai teaches all the limitations of the base claims as outlined above.
Further, Kavaklioglu teaches the device [0011, 0030, 0037-0037-0038, Fig. 2 — index aggregation routine 60 may be centrally located at a particular server, which may be maintained locally at the plant 10 or remotely from the plant 10. Alternatively, the index aggregation routine 60 may be distributed among several computers such as business system computers 35, maintenance computers 18, 22, maintenance planning computers 36] is further configured to perform an acquisition function to acquire the first data [0037 — an index aggregation routine 60 receives information from information sources which may run various routines (functions) and applications (functions) for providing status information regarding devices, loops, units, areas, etc. within a process plant.; 0041-0045 —index aggregation routine 60 may acquire weighting values related to each device, loop, sub-unit, unit, area, plant, etc. within a group by receiving each weighting value from another source or by creating each weighting value based on information from a variety of sources. For example, the index aggregation routine 60 may receive data relating to the impact and frequency of failure of each device; 0066 — In the case of calculating a PI for a loop, the system may, for example, compare the maximum or average loop error (i.e., the steady state error signal) to some predetermined minimum error value which, ideally, may be zero. In this manner, a small loop error may correspond to a PI value that is indicative of good performance], the second data [0037 — an index aggregation routine 60 receives information from information sources which may run various routines and applications for providing status information regarding devices, loops, units, areas, etc. within a process plant.; 0066 —FIG. 4 is an exemplary table that illustrates one manner in which the performance index (PI), the health index (HI), the variability index (VI) and the utilization index (UI) may or may not be generated for the device, loop, sub unit and unit levels of the system hierarchy; 0070 — the UI may be calculated for the loop, sub unit and unit levels, but may not necessarily be calculated for the device level. Generally speaking, the UI represents the degree to which a particular asset (e.g., a loop, a sub unit or a unit) is being exploited in comparison to its capacity or desired utilization. For example, the UI value may be based on the amount of time for which a unit, sub unit or loop is being used to perform control or produce outputs. Additionally or alternatively, the UI value may be based on the amount of material which is being processed by the loop], and/or the third data [0037 — an index aggregation routine 60 receives information from information sources which may run various routines and applications for providing status information regarding devices, loops, units, areas, etc. within a process plant.; 0070 — the UI may be calculated for the loop, sub unit and unit levels, but may not necessarily be calculated for the device level….Additionally or alternatively, the UI value may be based on the amount of material which is being processed by the loop].
Regarding claim 13, the combination of Kavaklioglu and Kawai teaches all the limitations of the base claims as outlined above.
Further, Kavaklioglu teaches the device [0011, 0030, 0037-0037-0038, Fig. 2 — index aggregation routine 60 may be centrally located at a particular server, which may be maintained locally at the plant 10 or remotely from the plant 10. Alternatively, the index aggregation routine 60 may be distributed among several computers such as business system computers 35, maintenance computers 18, 22, maintenance planning computers 36] is further configured to perform a determination function to determine the process indicator number based on the first data, the second data, and the third data, and/or to create a time profile of the process indicator number [0030, Fig. 2 — asset utilization expert 50 may include or execute index generation software 51 that creates indices associated with devices, like process control and instrumentation devices, power generation devices, rotating equipment, units, areas, etc, or that are associated with process control entities, like loops, etc. within the plant 10. The asset utilization expert 50 may further include or execute an index aggregation routine 60. The index aggregation routine 60 utilizes indices generated by the index generation routine 51 or other index generation routines to create indices associated with various levels within a process control system (current condition of a system), or more generally an asset utilization system, which may include one or more process control systems. The index aggregation routine 60 further includes a weighting value when creating an aggregate index associated with a process, unit, area; 0037-0038 — the index aggregation routine 60 receives information from various data sources, which may include data collectors, data generators or data tools including index generation routines 51… This information may include indices related to the health, performance, utilization and variability of a particular device, loop, unit, area, etc.; 0045-0051 — index aggregation routine 60 may calculate the aggregate index as a weighted average according to the following general equation… the aggregate index u is provided as a number from 0 to 100].
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Kavaklioglu and Kawai in view of Zhang et al. U.S. Patent Publication No. 20190384257 (hereinafter Zhang).
Regarding claim 2, the combination of Kavaklioglu and Kawai teaches all the limitations of the base claims as outlined above.
Further, Kavaklioglu teaches the determined process indicator number [0030, Fig. 2 — asset utilization expert 50 may include or execute index generation software 51 that creates indices associated with devices, like process control and instrumentation devices, power generation devices, rotating equipment, units, areas, etc, or that are associated with process control entities, like loops, etc. within the plant 10. The asset utilization expert 50 may further include or execute an index aggregation routine 60. The index aggregation routine 60 utilizes indices generated by the index generation routine 51 or other index generation routines to create indices associated with various levels within a process control system (current condition of a system), or more generally an asset utilization system, which may include one or more process control systems. The index aggregation routine 60 further includes a weighting value when creating an aggregate index associated with a process, unit, area; 0037-0038 — the index aggregation routine 60 receives information from various data sources, which may include data collectors, data generators or data tools including index generation routines 51… This information may include indices related to the health, performance, utilization and variability of a particular device, loop, unit, area, etc.; 0045-0051 — index aggregation routine 60 may calculate the aggregate index as a weighted average according to the following general equation… the aggregate index u is provided as a number from 0 to 100].
But the combination of Kavaklioglu and Kawai fails to clearly specify using the determined indicator number to determine whether to initiate at least one of maintenance, troubleshooting, cleaning, service, and repair work.
However, Zhang teaches using the determined indicator number to determine whether to initiate at least one of maintenance, troubleshooting, cleaning, service, and repair work [0036 — health indicator sequences 160 can be scores used for predictive maintenance on a type of automobile or industrial equipment. The multi-phase data-driven method can be used across different types of equipment and different industries (e.g., industrial equipment, automobiles, digital systems, etc.). In an example implementation, health indicator learning process 100 is applied once to a set or type of equipment that can be repeated applied to a data stream of observed equipment states to perform AD, FP, RUL, and OR (operation recommendation); 0049 — A health indicator score of 0.0 can indicate the equipment has failed and is no longer useful and/or requires repair and maintenance actions].
Kavaklioglu, Kawai and Zhang are analogous art. They relate to industrial control systems, particularly those including maintenance systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by the combination of Kavaklioglu and Kawai, by incorporating energy consumption in the process, as taught by Zhang.
One of ordinary skill in the art would have been motivated to do this modification in order to automatically determine when maintenance is required and avoid undesired health degradation, as suggested by Zhang [0029-0036, 0049].
Claim(s) 3 and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Kavaklioglu and Kawai in view of Sverdlov et al. U.S. Patent Publication No. 20220089237 (hereinafter Sverdlov).
Regarding claim 3, the combination of Kavaklioglu and Kawai teaches all the limitations of the base claims as outlined above.
Further, Kavaklioglu teaches acquiring the first data includes acquiring at least one of the following: faults in the system [0041-0045 —index aggregation routine 60 may acquire weighting values related to each device, loop, sub-unit, unit, area, plant, etc. within a group by receiving each weighting value from another source or by creating each weighting value based on information from a variety of sources. For example, the index aggregation routine 60 may receive data relating to the impact and frequency of failure of each device; 0066 — In the case of calculating a PI for a loop, the system may, for example, compare the maximum or average loop error (i.e., the steady state error signal) to some predetermined minimum error value which, ideally, may be zero. In this manner, a small loop error may correspond to a PI value that is indicative of good performance].
But the combination of Kavaklioglu and Kawai fails to clearly specify at least one of the following: first faults in the system which lead to a process stoppage of the process; second faults in the system which lead to an extension of the process in time; and third faults in the system that do not lead to any extension in time and to no process stoppage of the process.
However, Sverdlov teaches at least one of the following: first faults in the system which lead to a process stoppage of the process; second faults in the system which lead to an extension of the process in time; and third faults in the system that do not lead to any extension in time and to no process stoppage of the process [0184 — This is in effect a conveyor belt process, in which a single failure can stop the entire process].
Kavaklioglu, Kawai and Sverdlov are analogous art. They relate to industrial control systems, particularly those including maintenance systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to simply substitute the known process stoppage type faults of Sverdlov for the known faults of Kavaklioglu and Kawai for the predictable result of a method involving faults that lead to process stoppage.
Regarding claim 15, the combination of Kavaklioglu and Kawai teaches all the limitations of the base claims as outlined above and this claim is otherwise rejected based on the same rationale as claim 3.
Regarding claim 16, the combination of Kavaklioglu, Kawai and Sverdlov teaches all the limitations of the base claims as outlined above.
Further, Kavaklioglu teaches the device [0011, 0030, 0037-0037-0038, Fig. 2 — index aggregation routine 60 may be centrally located at a particular server, which may be maintained locally at the plant 10 or remotely from the plant 10. Alternatively, the index aggregation routine 60 may be distributed among several computers such as business system computers 35, maintenance computers 18, 22, maintenance planning computers 36] is further configured to perform an analysis function for analyzing at least one of the first faults, the second faults, and the third faults [0041 — the importance of a device, loop, sub-unit, unit, area, etc., and its corresponding weighting value, is based on two contributing factors: the impact on the group when the asset fails and the frequency of failure. For example, a device that has little impact on an area when it fails may be weighted lower than a device that has a high impact on an area during failure. Likewise, a device that has a low frequency of failure may be weighted lower than a device with a high frequency of failure. The impact and the frequency of failure may be quantified, with the product of the impact and frequency of failure resulting in the weighting value].
Claim(s) 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Kavaklioglu, Kawai and Sverdlov in view of Broadwater et al. U.S. Patent No. 5600576 (hereinafter Broadwater).
Regarding claim 9, the combination of Kavaklioglu, Kawai and Sverdlov teaches all the limitations of the base claims as outlined above.
Further, Kavaklioglu teaches analyzing the first faults, the second faults, and/or the third fault [0041 — the importance of a device, loop, sub-unit, unit, area, etc., and its corresponding weighting value, is based on two contributing factors: the impact on the group when the asset fails and the frequency of failure. For example, a device that has little impact on an area when it fails may be weighted lower than a device that has a high impact on an area during failure. Likewise, a device that has a low frequency of failure may be weighted lower than a device with a high frequency of failure. The impact and the frequency of failure may be quantified, with the product of the impact and frequency of failure resulting in the weighting value].
But the combination of Kavaklioglu and Kawai fails to clearly specify analyzing the first faults, the second faults, and/or the third faults including: associating, during the analysis, events in the system that are related to one another in terms of time; and making, during the analysis, an association to environmental conditions of the system.
However, Broadwater teaches analyzing the first faults, the second faults, and/or the third faults including: associating, during the analysis, events in the system that are related to one another in terms of time; and making, during the analysis, an association to environmental conditions of the system [col. 2 lines 12-40 — It is an additional object of the invention to enable maintenance personnel to use the collected data to identify and analyze system and subsystem events, including faults… a time stress measurement device (TSMD) is provided comprising environmental data collecting means for collecting environmental data corresponding to a plurality of environmental influences applied to a system being measured; event data collecting means for collecting event data corresponding to an event experienced by the system being measured; processing means for time-stamping the collected environmental data with a time when the environmental data is collected, for time-stamping the collected event data with a time when the event data is collected, and for comparing the collected environmental data to preset environmental data thresholds; and storage means for storing the time-stamped environmental data and the time-stamped fault data; col. 6 lines 31-56 —The primary processing algorithm of the TSMD is the Event Signature which time tags environmental stress data before, during, and after an event such as a fault or overstress event, and places it in non-volatile memory. The Event Signature consists of several data structures that share a time stamp as a key field. If a system fault or failure is detected, or if a software set environmental threshold is exceeded, the data resident in the cyclical buffer 74 is time tagged with the BIT event code, and is placed in the Event Signature Data Structure 84; Abstract, claim 1].
Kavaklioglu, Kawai, Sverdlov and Broadwater are analogous art. They relate to industrial control systems, particularly those including maintenance systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by the combination of Kavaklioglu, Kawai, and Sverdlov by incorporating energy consumption in the process, as taught by Broadwater.
One of ordinary skill in the art would have been motivated to do this modification in order to assist with understanding and correcting environmentally related system failures, as suggested by Broadwater [col. 1 lines 5-12 and 54-63].
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over the combination of Kavaklioglu and Kawai in view of Mehta et al. U.S. Patent Publication No. 20090112335 (hereinafter Mehta).
Regarding claim 10, the combination of Kavaklioglu and Kawai teaches all the limitations of the base claims as outlined above.
Further, Kavaklioglu teaches the determined process indicator number [0030, Fig. 2 — asset utilization expert 50 may include or execute index generation software 51 that creates indices associated with devices, like process control and instrumentation devices, power generation devices, rotating equipment, units, areas, etc, or that are associated with process control entities, like loops, etc. within the plant 10. The asset utilization expert 50 may further include or execute an index aggregation routine 60. The index aggregation routine 60 utilizes indices generated by the index generation routine 51 or other index generation routines to create indices associated with various levels within a process control system (current condition of a system), or more generally an asset utilization system, which may include one or more process control systems. The index aggregation routine 60 further includes a weighting value when creating an aggregate index associated with a process, unit, area; 0037-0038 — the index aggregation routine 60 receives information from various data sources, which may include data collectors, data generators or data tools including index generation routines 51… This information may include indices related to the health, performance, utilization and variability of a particular device, loop, unit, area, etc.; 0045-0051 — index aggregation routine 60 may calculate the aggregate index as a weighted average according to the following general equation… the aggregate index u is provided as a number from 0 to 100].
But the combination of Kavaklioglu and Kawai fails to clearly specify creating a time profile of the process indicator number; and comparing the time profile of the process indicator number with a preceding time profile of the process indicator number.
However, Mehta teaches creating a time profile of the process indicator number; and comparing the time profile of the process indicator number with a preceding time profile of the process indicator number [0121 — Historical performance reporting may be provided to display how a control loop has performed over a user-specified period of time… control performance monitoring information may be provided in any desired form, including a number of customized display interfaces and report… reports or interfaces may be customized for management summaries with, for instance, an overall weighted performance index for plant-wide and individual process units, trends (time profile) and/or tables comparing the current period with prior periods].
Kavaklioglu, Kawai and Mehta are analogous art. They relate to industrial control systems, particularly those including maintenance systems.
Therefore at the time the invention was made, it would have been obvious to a person of ordinary skill in the art to modify the above method, as taught by the combination of Kavaklioglu and Kawai, by incorporating energy consumption in the process, as taught by Mehta.
One of ordinary skill in the art would have been motivated to do this modification in order to determine assets requiring maintenance soon, as suggested by Mehta [0121-0127], and thus avoid future failures or the undesired effects of system degradation.
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
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BERNARD G. LINDSAY whose telephone number is (571)270-0665. The examiner can normally be reached Monday through Friday from 8:30 AM to 5:30 PM EST.
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/BERNARD G LINDSAY/
Primary Examiner, Art Unit 2119