Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception without significantly more. A subject matter eligibility analysis is set forth below. See MPEP 2106.
Specifically, representative Claim 1 recites:
A method of managing alarms in a process control system, the method comprising:
receiving, by a shelving decision support engine, industrial process information collected from the process control system, wherein the industrial process information includes an indication of an alarm associated with at least one industrial process;
storing the collected industrial process information in one or more decision support databases;
further storing historical information relating to past alarm shelving decisions and operator specific decisions in the one or more decision support databases;
executing, by the shelving decision support engine, a weighting algorithm on the alarm based on the industrial process information and the historical information stored in the decision support databases, wherein the weighting algorithm is a function of one or more relevant factors associated with the at least one industrial process having weights assigned thereto;
generating, by the shelving decision support engine, a probabilistic determination of alarm priority for shelving the alarm as a function of the weighting algorithm; and
automatically shelving the alarm for a determined period of time in response to the probabilistic determination indicating the alarm is to be shelved.
The claim limitations in the abstract idea have been highlighted in bold above; the remaining limitations are “additional elements.”
Similar limitations comprise the abstract idea of Claim 13.
Under Step 1 of the analysis, Claim 1 is a method claim, and Claim 13 is a system claim.
Under Step 2A, prong 1: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
In the instant case, Claim 1 is found to recite at least one judicial exception (i.e. abstract idea), that being a Mental Process and/or a Mathematical Concepts. This can be seen in the claim limitations of executing a weighting algorithm, and generating a probabilistic determination, which are the judicial exception of a mental process because these limitations are merely data observations, evaluations, and/or judgements in order to determine an alarm priority, and is capable of being performed mentally and/or with the aid of pen and paper. Additionally, the aforementioned limitations recite mathematical calculations, i.e., a weighting algorithm and a probabilistic determination, in order to determine the alarm priority.
Similar limitations comprise the abstract ideas of Claim 13.
Step 2A, prong 2 of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception(s) into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
In addition to the abstract ideas recited in claim 1, the claimed method recites additional elements including “receiving, by a shelving decision support engine, industrial process information collected from the process control system, wherein the industrial process information includes an indication of an alarm associated with at least one industrial process”; “storing the collected industrial process information in one or more decision support databases”; “further storing historical information relating to past alarm shelving decisions and operator specific decisions in the one or more decision support databases”, a shelving decision support engine, and “automatically shelving the alarm for a determined period of time in response to the probabilistic determination indicating the alarm is to be shelved”. However, the receiving, storing, storing, and shelving steps are found to be merely data gathering and output steps, which are recited at a high level of generality, and thus merely amount to “insignificant extra-solution” activity(ies). See MPEP 2106.05(g) “Insignificant Extra-Solution Activity. Further, the shelving decision support engine merely amounts to performing the executing and generating steps by a generic computer, however this is found to be equivalent to adding the words “apply it” and mere instructions to apply a judicial exception on a general purpose computer does not integrate the abstract idea into a practical application. See MPEP 2106.05(f).
The generic data gathering, processing, and output steps, are recited at such a high level of generality (e.g. using a shelving decision support engine) that it represents no more than mere instructions to apply the judicial exceptions on a computer. It can also be viewed as nothing more than an attempt to generally link the use of the judicial exceptions to the technological environment of a computer. Noting MPEP 2106.04(d)(I): “It is notable that mere physicality or tangibility of an additional element or elements is not a relevant consideration in Step 2A Prong Two. As the Supreme Court explained in Alice Corp., mere physical or tangible implementation of an exception does not guarantee eligibility. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1983-84 (2014) ("The fact that a computer ‘necessarily exist[s] in the physical, rather than purely conceptual, realm,’ is beside the point")”.
Thus, under Step 2A, prong 2 of the analysis, even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception. No specific practical application is associated with the claimed method.
Under Step 2B, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements, as described above with respect to Step 2A Prong 2, merely amount to a general purpose computer system that attempts to apply the abstract idea in a technological environment, limiting the abstract idea to a particular field of use, and/or merely performs insignificant extra-solution activit(ies). Such insignificant extra-solution activity, e.g. data gathering and output, when re-evaluated under Step 2B is further found to be well-understood, routine, and conventional as evidenced by MPEP 2106.05(d)(II). Therefore, similarly the combination and arrangement of the above identified additional elements when analyzed under Step 2B also fails to necessitate a conclusion that Claims 1 and 13 amount to significantly more than the abstract idea.
With regards to the dependent claims 2-12 and 14-24 merely further expand upon the algorithm/abstract idea and do not set forth further additional elements that integrate the recited abstract idea into a practical application or amount to significantly more. Therefore, these claims are found ineligible for the reasons described for parent claims 1 and 13. Specifically, the dependent Claims merely recite further details of the insignificant extra-solution activity, e.g., the data gathering and output steps, and/or additional details of the abstract idea.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-2, 7-11, 13-14, and 19-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cote et al (U.S. Pub. No. 2023/0076662, hereinafter “Cote”, cited on Applicant’s IDS dated 11/13/2024) in view of Childs et al (U.S. Pub. No. 2016/0300475, hereinafter “Childs”).
Regarding Claim 1, Cote teaches a method of managing alarms in a process control system (Fig. 3, Fig. 8), the method comprising: receiving, by a shelving decision support engine, industrial process information collected from the process control system, wherein the industrial process information includes an indication of an alarm associated with at least one industrial process (Fig. 8, block 102; paragraph [0001], alarm suppression is equated to alarm shelving, as evidenced by paragraphs [0064] and [0066] of Childs; paragraph [0002], NOC is equated to industrial process); storing the collected industrial process information in one or more decision support databases (Figs. 2-3, data 14); further storing historical information relating to past alarm shelving decisions and operator specific decisions in the one or more decision support databases (Figs 2-3, labelled observations 12; paragraphs [0030] and [0033]-[0037], ticket data); executing, by the alarm shelving decision support engine, a weighting algorithm on the alarm based on the industrial process information and the historical information stored in the decision support databases, wherein the weighting algorithm is a function of one or more relevant factors associated with the at least one industrial process having weights assigned thereto (Figs. 2-3, self-adapting auto-ML system 10, Fig. 8, block 104); generating, by the alarm shelving decision support engine, a probabilistic determination of priority for shelving the alarm as a function of the weighting algorithm (Figs. 2-3, predictions 18); and automatically shelving the alarm in response to the probabilistic determination indicating the alarm is to be shelved (Fig. 8, block 106).
Cote does not specifically teach shelving the alarm for a determined period of time. However, Cote does teach alarm suppression, which is equated to alarm shelving (Fig. 8, block 106). Further, Childs teaches shelving, or suppressing, the alarm for a determined period of time (paragraphs [0064]-[0066], Claim 3, determination of maximum shelf time). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the shelf time of Childs in the system of Cote, in order to avoid overloading an operator (see Childs, paragraph [0003]) and document alarm philosophy, rationale, and prioritization rules (see Childs, paragraphs [0022]-[0023]).
Regarding Claim 2, Cote in view of Childs teaches everything that is claimed above with respect to Claim 1. Cote further teaches wherein generating the probabilistic determination comprises evaluating the alarm to determine a shelving probability of the alarm being shelved, the shelving probability being based on the weighting algorithm taking into account the industrial process information and the historical information stored in the decision support databases (Fig. 8, blocks 104 and 106; whether the alarm is suppressed or not is equated to shelving probability, e.g., either 0% or 100%).
Cote does not specifically teach determining an estimated time duration before the alarm is un-shelved if the alarm is to be shelved. However, Childs teaches determining an estimated time duration before the alarm is un-shelved if the alarm is to be shelved (paragraphs [0064]-[0066], Claim 3, determination of maximum shelf time). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the maximum shelf time of Childs in the system of Cote, in order to avoid overloading a plant operator (see Childs, paragraph [0003]) and document alarm philosophy, rationale, and prioritization rules (see Childs, paragraphs [0022]-[0023]).
Regarding Claim 7, Cote in view of Childs teaches everything that is claimed above with respect to Claim 1. Cote further teaches wherein executing the weighting algorithm comprises executing a machine-learned model (Figs. 2-3, self-adapting auto-ML system 10).
Regarding Claim 8, Cote in view of Childs teaches everything that is claimed above with respect to Claim 7. Cote further teaches wherein executing the machine-learned model comprises training the machine-learned model based on the historical information stored in the decision support databases (Fig. 8, block 108; Figs. 2-3, data 14 and labelled observations 12).
Regarding Claim 9, Cote in view of Childs teaches everything that is claimed above with respect to Claim 1. Cote further teaches wherein the decision support databases store the one or more relevant factors associated with the at least one industrial process (Figs. 2-3, data 14 and labelled observations 12), including one or more of: (a) history of alarms and instances an alarm of the same type of the present alarm has been identified as a nuisance alarm (paragraphs [0041]-[0042], and [0053]-[0054], alarms labeled as non-important alarm); (b) shelving history of alarms; (c) simple/complex condition set for alarm shelving; (d) maintenance schedule for equipment; (e) calibration schedule for equipment; (f) state of equipment before and during the alarm to analyze an impact on the equipment; (g) past state of the equipment before, during, and post the alarm to provide a rationale; (h) equipment diagnostics; and (i) equipment conditions and current state thereof (optional due to “one or more of”).
Regarding Claim 10, Cote in view of Childs teaches everything that is claimed above with respect to Claim 9. Cote further teaches wherein each of the one or more relevant factors has an associated weighting for use in the weighting algorithm (paragraphs [0041]-[0042], and [0053]-[0054], alarms labeled in labelled observations 12 as non-important alarms, which is used to train self-adapting auto-ML system 10, which makes alarm determinations based on machine learned weights).
Regarding Claim 11, Cote in view of Childs teaches everything that is claimed above with respect to Claim 1. Cote further teaches further comprising: extracting possible alarm types from one or more alarm databases (paragraphs [0026], [0028], Figs. 1A-1B, alarm types); evaluating the possible alarm types to identify alarm types relevant to the at least one industrial process (Figs. 2-3, labelled observations 12; paragraphs [0037] and [0059], important alarms equated to relevance); and identifying the one or more relevant factors to consider in the weighting algorithm based, at least in part, on the identified alarm types (Figs. 2-3, self-adapting auto-ML system 10, Fig. 8, block 108).
Regarding Claim 13, Cote teaches an alarm management system (Figs. 2-3) comprising: a shelving decision support engine (Figs. 2-3, self-adapting auto-ML system 10) receiving and responsive to industrial process information collected from a process control system, the industrial process information including an indication of an alarm associated with at least one industrial process (Fig. 8, block 102; paragraph [0001], alarm suppression is equated to alarm shelving, as evidenced by paragraphs [0064] and [0066] of Childs; paragraph [0002], NOC is equated to industrial process); one or more decision support databases storing the collected industrial process information and further storing historical information relating to past alarm shelving decisions and operator specific decisions (Figs. 2-3, data 14, labelled observations 12; paragraphs [0030] and [0033]-[0037], ticket data); a memory storing computer-executable instructions (Fig. 9) that, when executed by the shelving decision support engine, configure the shelving decision support engine (Figs. 2-3, self-adapting auto-ML system 10) for: executing a weighting algorithm on the alarm based on the industrial process information and the historical information stored in the decision support databases, wherein the weighting algorithm is a function of one or more relevant factors associated with the at least one industrial process having weights assigned thereto (Figs. 2-3, self-adapting auto-ML system 10, Fig. 8, block 104); generating a probabilistic determination of alarm priority for shelving the alarm as a function of the weighting algorithm (Figs. 2-3, predictions 18); and automatically shelving the alarm in response to the probabilistic determination indicating the alarm is to be shelved (Fig. 8, block 106).
Cote does not specifically teach shelving the alarm for a determined period of time. However, Cote does teach alarm suppression, which is equated to alarm shelving (Fig. 8, block 106). Further, Childs teaches shelving, or suppressing, the alarm for a determined period of time (paragraphs [0064]-[0066], Claim 3, determination of maximum shelf time). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the shelf time of Childs in the system of Cote, in order to avoid overloading an operator (see Childs, paragraph [0003]) and document alarm philosophy, rationale, and prioritization rules (see Childs, paragraphs [0022]-[0023]).
Regarding Claim 14, Cote in view of Childs teaches everything that is claimed above with respect to Claim 13. Cote further teaches wherein generating the probabilistic determination comprises evaluating the alarm to determine a shelving probability of the alarm being shelved, the shelving probability being based on the weighting algorithm taking into account the industrial process information and the historical information stored in the decision support databases (Fig. 8, blocks 104 and 106; whether the alarm is suppressed or not is equated to shelving probability, e.g., either 0% or 100%).
Cote does not specifically teach determining an estimated time duration before the alarm is un-shelved if the alarm is to be shelved. However, Childs teaches determining an estimated time duration before the alarm is un-shelved if the alarm is to be shelved (paragraphs [0064]-[0066], Claim 3, determination of maximum shelf time). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the maximum shelf time of Childs in the system of Cote, in order to avoid overloading a plant operator (see Childs, paragraph [0003]) and document alarm philosophy, rationale, and prioritization rules (see Childs, paragraphs [0022]-[0023]).
Regarding Claim 19, Cote in view of Childs teaches everything that is claimed above with respect to Claim 13. Cote further teaches wherein executing the weighting algorithm comprises executing a machine-learned model (Figs. 2-3, self-adapting auto-ML system 10).
Regarding Claim 20, Cote in view of Childs teaches everything that is claimed above with respect to Claim 19. Cote further teaches wherein the computer-executable instructions, when executed by the shelving decision support engine, further configure the shelving decision support engine for training the machine-learned model based on the historical information stored in the decision support databases (Fig. 8, block 108; Figs. 2-3, data 14 and labelled observations 12).
Regarding Claim 21, Cote in view of Childs teaches everything that is claimed above with respect to Claim 13. Cote further teaches wherein the decision support databases store the one or more relevant factors associated with the at least one industrial process (Figs. 2-3, data 14 and labelled observations 12), including one or more of: (a) history of alarms and instances an alarm of the same type of the present alarm has been identified as a nuisance alarm (paragraphs [0041]-[0042], and [0053]-[0054], alarms labeled as non-important alarm); (b) shelving history of alarms; (c) simple/complex condition set for alarm shelving; (d) maintenance schedule for equipment; (e) calibration schedule for equipment; (f) state of equipment before and during the alarm to analyze an impact on the equipment; (g) past state of the equipment before, during, and post the alarm to provide a rationale; (h) equipment diagnostics; and (i) equipment conditions and current state thereof (optional due to “one or more of”).
Regarding Claim 22, Cote in view of Childs teaches everything that is claimed above with respect to Claim 21. Cote further teaches wherein each of the one or more relevant factors has an associated weighting for use in the weighting algorithm (paragraphs [0041]-[0042], and [0053]-[0054], alarms labeled in labelled observations 12 as non-important alarms, which is used to train self-adapting auto-ML system 10, which makes alarm determinations based on machine learned weights).
Regarding Claim 23, Cote in view of Childs teaches everything that is claimed above with respect to Claim 13. Cote further teaches wherein the computer-executable instructions, when executed by the shelving decision support engine, further configure the shelving decision support engine for: extracting possible alarm types from one or more alarm databases (paragraphs [0026], [0028], Figs. 1A-1B, alarm types); evaluating the possible alarm types to identify alarm types relevant to the at least one industrial process (Figs. 2-3, labelled observations 12; paragraphs [0037] and [0059], important alarms equated to relevance); and identifying the one or more relevant factors to consider in the weighting algorithm based, at least in part, on the identified alarm types (Figs. 2-3, self-adapting auto-ML system 10, Fig. 8, block 108).
Claim(s) 3-6 and15-18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cote in view of Childs and Srinivasan et al (U.S. Pub. No. 2018/0322770, hereinafter “Srinivasan”).
Regarding Claim 3, Cote in view of Childs teaches everything that is claimed above with respect to Claim 2. Cote further teaches further comprising providing, in response to the shelving probability exceeding a predetermined threshold, a shelving of the alarm (Fig. 8, blocks 104 and 106; whether the alarm is suppressed or not is equated to shelving probability, e.g., either 0% or 100%; 0% is equated to predetermined threshold). Cote does not specifically teach providing a rationale for the alarm being shelved and relevant information supporting the rationale. However, Srinivasan teaches providing a rationale for the alarm being shelved and relevant information supporting the rationale (paragraphs [0067], [0068], [0073], and [0076], rationalization for alarm suppression). It would have been obvious to include the alarm rationalizations of Srinivasan in the system of Cote, in order to suppress duplicate alarms (paragraph [0067]) and reduce alarms (paragraph [0073]).
Regarding Claim 4, Cote in view of Childs and Srinivasan teaches everything that is claimed above with respect to Claim 3. Cote does not specifically teach receiving, by the shelving decision support engine, operator input assessing the shelving probability in view of the provided alarm rationale and relevant information supporting the alarm rationale; and adjusting, by the shelving decision support engine, the weighting algorithm in response to the operator input assessing the shelving probability. However, Srinivasan teaches receiving, by the shelving decision support engine, operator input assessing the shelving probability in view of the provided alarm rationale and relevant information supporting the alarm rationale; and adjusting, by the shelving decision support engine, the weighting algorithm in response to the operator input assessing the shelving probability (paragraphs [0067], [0068], [0073], [0076]-[0078], alarm rationalizations are presented to user for approval; after user approves alarm rationalizations, they are used to suppress future alarms, which is equated to claimed adjusting). It would have been obvious to include the alarm rationalizations of Srinivasan in the system of Cote, in order to suppress duplicate alarms (paragraph [0067]) and reduce alarms (paragraph [0073]).
Regarding Claim 5, Cote in view of Childs and Srinivasan teaches everything that is claimed above with respect to Claim 4. Cote further teaches wherein receiving operator input comprises analyzing operator actions to learn and capture knowledge of the operator, and wherein adjusting the weighting algorithm is based on the learned and captured knowledge of operator (paragraphs [0030] and [0033]-[0037], NOC ticket data, which is used to train and update the AI/ML models, would include operator actions, and learned and captured knowledge of operators).
Regarding Claim 6, Cote in view of Childs and Srinivasan teaches everything that is claimed above with respect to Claim 3. Cote does not specifically teach further comprising: in response to determining the alarm rationale is acceptable, determining if the alarm should be shelved and for what period of time the alarm should be shelved; and in response to determining the alarm should be shelved, shelving the alarm for the determined period of time. However, Srinivasan teaches in response to determining the alarm rationale is acceptable, determining if the alarm should be shelved; and in response to determining the alarm should be shelved, shelving the alarm (paragraphs [0067], [0068], [0073], [0076]-[0078], alarm rationalizations are presented to user for approval; after user approves alarm rationalizations, which is equated to claimed determination of acceptability, they are used to suppress future alarms). It would have been obvious to include the alarm rationalizations of Srinivasan in the system of Cote, in order to suppress duplicate alarms (paragraph [0067]) and reduce alarms (paragraph [0073]).
Cote in view of Srinivasan does not specifically teach determining for what period of time the alarm should be shelved; and in response to determining the alarm should be shelved, shelving the alarm for the determined period of time. However, Childs determining for what period of time the alarm should be shelved; and in response to determining the alarm should be shelved, shelving the alarm for the determined period of time (paragraphs [0064]-[0066], Claim 3, determination of maximum shelf time for shelved alarms). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the maximum shelf time of Childs in the system of Cote and Srinivasan, in order to avoid overloading a plant operator (see Childs, paragraph [0003]) and document alarm philosophy, rationale, and prioritization rules (see Childs, paragraphs [0022]-[0023]).
Regarding Claim 15, Cote in view of Childs teaches everything that is claimed above with respect to Claim 14. Cote further teaches wherein the computer-executable instructions stored in the memory, when executed by the shelving decision support engine, further configure the shelving decision support engine for providing, in response to the shelving probability exceeding a predetermined threshold, a shelving of the alarm (Fig. 8, blocks 104 and 106; whether the alarm is suppressed or not is equated to shelving probability, e.g., either 0% or 100%; 0% is equated to predetermined threshold). Cote does not specifically teach providing a rationale for the alarm being shelved and relevant information supporting the rationale. However, Srinivasan teaches providing a rationale for the alarm being shelved and relevant information supporting the rationale (paragraphs [0067], [0068], [0073], and [0076], rationalization for alarm suppression). It would have been obvious to include the alarm rationalizations of Srinivasan in the system of Cote, in order to suppress duplicate alarms (paragraph [0067]) and reduce alarms (paragraph [0073]).
Regarding Claim 16, Cote in view of Childs and Srinivasan teaches everything that is claimed above with respect to Claim 15. Cote does not specifically teach wherein the computer-executable instructions stored in the memory, when executed by the shelving decision support engine, further configure the shelving decision support engine for: receiving, by the shelving decision support engine, operator input assessing the shelving probability in view of the provided alarm rationale and relevant information supporting the alarm rationale; and adjusting, by the shelving decision support engine, the weighting algorithm in response to the operator input assessing the shelving probability. However, Srinivasan teaches receiving, by the shelving decision support engine, operator input assessing the shelving probability in view of the provided alarm rationale and relevant information supporting the alarm rationale; and adjusting, by the shelving decision support engine, the weighting algorithm in response to the operator input assessing the shelving probability (paragraphs [0067], [0068], [0073], [0076]-[0078], alarm rationalizations are presented to user for approval; after user approves alarm rationalizations, they are used to suppress future alarms, which is equated to claimed adjusting). It would have been obvious to include the alarm rationalizations of Srinivasan in the system of Cote, in order to suppress duplicate alarms (paragraph [0067]) and reduce alarms (paragraph [0073]).
Regarding Claim 17, Cote in view of Childs and Srinivasan teaches everything that is claimed above with respect to Claim 16. Cote further teaches wherein receiving operator input comprises analyzing operator actions to learn and capture knowledge of the operator, and wherein adjusting the weighting algorithm is based on the learned and captured knowledge of operator (paragraphs [0030] and [0033]-[0037], NOC ticket data, which is used to train and update the AI/ML models, would include operator actions, and learned and captured knowledge of operators).
Regarding Claim 18, Cote in view of Childs and Srinivasan teaches everything that is claimed above with respect to Claim 15. Cote does not specifically teach wherein the computer-executable instructions stored in the memory, when executed by the shelving decision support engine, further configure the shelving decision support engine for: in response to determining the alarm rationale is acceptable, determining if the alarm should be shelved and for what period of time the alarm should be shelved; and in response to determining the alarm should be shelved, shelving the alarm for the determined period of time. However, Srinivasan teaches in response to determining the alarm rationale is acceptable, determining if the alarm should be shelved; and in response to determining the alarm should be shelved, shelving the alarm (paragraphs [0067], [0068], [0073], [0076]-[0078], alarm rationalizations are presented to user for approval; after user approves alarm rationalizations, which is equated to claimed determination of acceptability, they are used to suppress future alarms). It would have been obvious to include the alarm rationalizations of Srinivasan in the system of Cote, in order to suppress duplicate alarms (paragraph [0067]) and reduce alarms (paragraph [0073]).
Cote in view of Srinivasan does not specifically teach determining for what period of time the alarm should be shelved; and in response to determining the alarm should be shelved, shelving the alarm for the determined period of time. However, Childs determining for what period of time the alarm should be shelved; and in response to determining the alarm should be shelved, shelving the alarm for the determined period of time (paragraphs [0064]-[0066], Claim 3, determination of maximum shelf time for shelved alarms). It would have been obvious to one skilled in the art before the effective filing date of the invention to include the maximum shelf time of Childs in the system of Cote and Srinivasan, in order to avoid overloading a plant operator (see Childs, paragraph [0003]) and document alarm philosophy, rationale, and prioritization rules (see Childs, paragraphs [0022]-[0023]).
Claim(s) 12 and 24 is/are rejected under 35 U.S.C. 103 as being unpatentable over Cote in view of Childs and Singh et al (U.S. Pub. No. 2021/0177341, hereinafter “Singh”).
Regarding Claim 12, Cote in view of Childs teaches everything that is claimed above with respect to Claim 1. Cote further teaches evaluating, by the shelving decision support engine, if the alarm is a an important alarm (Fig. 8, block 104, important alarm) or another alarm type (Fig. 8, block 104, non-important alarm); and in response to determining the alarm is an important alarm, providing a notification to the operator indicating the alarm is an important alarm (Fig. 8, block 106).
Cote does not specifically teach that the important alarm is a Human Safety Environment (HSE) alarm. However, Singh teaches displaying HSE alerts in paragraph [0101]. It would have been obvious to one skilled in the art before the effective filing date of the invention to include the HSE alerts of Singh in the system of Cote, in order to trigger a manager to take appropriate action (see Singh, paragraph [0101]).
Regarding Claim 24, Cote in view of Childs teaches everything that is claimed above with respect to Claim 1. Cote further teaches wherein the computer-executable instructions stored in the memory, when executed by the shelving decision support engine, further configure the shelving decision support engine for: evaluating, by the shelving decision support engine, if the alarm is a an important alarm (Fig. 8, block 104, important alarm) or another alarm type (Fig. 8, block 104, non-important alarm); and in response to determining the alarm is an important alarm, providing a notification to the operator indicating the alarm is an important alarm (Fig. 8, block 106).
Cote does not specifically teach that the important alarm is a Human Safety Environment (HSE) alarm. However, Singh teaches displaying HSE alerts in paragraph [0101]. It would have been obvious to one skilled in the art before the effective filing date of the invention to include the HSE alerts of Singh in the system of Cote, in order to trigger a manager to take appropriate action (see Singh, paragraph [0101]).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CYNTHIA L DAVIS whose telephone number is (571)272-1599. The examiner can normally be reached Monday-Friday, 7am to 3pm.
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/CYNTHIA L DAVIS/Examiner, Art Unit 2857
/SHELBY A TURNER/Supervisory Patent Examiner, Art Unit 2857
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