DETAILED ACTION
The present office action is responsive to the applicant’s filling on 06/28/2023.
The application has claims 1-20 present. All present claims have been examined.
The Disclosure Statement document (IDS) and references submitted by applicant on 09/08/2023 have been reviewed and taken into consideration by the examiner.
This action is made Non-Final.
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 .
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. The entire reference is considered to provide disclosure relating to the claimed invention. The claims & only the claims form the metes & bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent & spirit of compact prosecution.
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.
Regarding claims 1, 12 and 20 the phrase, "alarm insight data associated with respective alarm count reduction predictions" renders the claim indefinite because it is unclear what the metes and bounds are with count reduction prediction. See MPEP § 2173.05(d). For purpose of examination, it will be interpreted as suggestion based on received data.
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-5, 7, 11-16 and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Srinivasan et al. (US 20180322770).
In regards to claims (1, 12 and 20), Srinivasan discloses a system, comprising: one or more processors; a memory; and one or more programs stored in the memory, the one or more programs comprising instructions configured to: transmit, to a server system, a request to obtain alarm tuning recommendation data for one or more alarm configuration parameters related to one or more industrial processes in an industrial environment in response to an action performed with respect to a first user interface configuration for an interactive user interface (see para 6-7, 36-37: industrial process control system and alarm management, on para 45-46: manage tool allows user to manage alarm. Para 56-61 teaches configuration of the alarm within a user interface. Determining when user selects a proposed setting for the alarm), wherein the request comprises one or more alarm identifiers related to the one or more industrial processes; in response to the request: receive the alarm tuning recommendation data from the server system, wherein the alarm tuning recommendation data is configured based on the one or more alarm identifiers and alarm insight data associated with respective alarm count reduction predictions for the one or more alarm configuration parameters (see para 36-37: industrial process control system and alarm management, 56-64: teaches reduction of count and providing proposed setting and tuning the alarm based on the received data); alter the first user interface configuration for the interactive user interface based on the alarm tuning recommendation data to provide a second user interface configuration for the interactive user interface, wherein the second user interface configuration comprises respective interactive display elements related to the one or more alarm identifiers, and wherein the respective interactive display elements for the second user interface configuration are rendered via the interactive user interface based on the alarm tuning recommendation data (see at least para 36, 60-68: after selecting and adjusting alarm, the system calculates and analyses selection and data and provides other interface which provides a menu or list where the user can select and approve additional alarm settings and relationships).
In regards to claims (2 and 13), Srinivasan discloses wherein the alarm tuning recommendation data comprises predicted impact data associated with respective impact classifications for the one or more industrial processes by tuning respective alarm configuration parameters for the one or more industrial processes, and the one or more programs further comprising instructions configured to: arrange the respective interactive display elements related to the one or more alarm identifiers based on the predicted impact data (see para 31, 65-67: predicted impact for classification and duplicate alarms and presenting the user with an interactive display where the user can select and approve additional alarm settings).
In regards to claims (3 and 14). Srinivasan discloses wherein the alarm tuning recommendation data comprises predicted optimization data associated with an estimated degree of reduction in a number of alarms based on tuning of respective alarm configuration parameters for the one or more industrial processes, and the one or more programs further comprising instructions configured to: arrange the respective interactive display elements related to the one or more alarm identifiers based on the predicted optimization data (see para 67 “presenting a list of potential duplicate alarms along with the degree of the relationship and potential impact/reduction on alarm count resulting from rationalization (suppression of duplicate alarms). This information could be presented to the user as a list, where the user could select and approve the appropriate duplicate alarm relationships”).
In regards to claims (4 and 15), Srinivasan discloses wherein the alarm tuning recommendation data comprises predicted industrial operations metrics data associated with a predicted performance of the one or more industrial processes based on tuning of respective configuration parameters for the one or more industrial processes, and the one or more programs further comprising instructions configured to: arrange the respective interactive display elements related to the one or more alarm identifiers based on the predicted industrial operations metrics data (see at least para 65-68, 71-78, 80-82, 103-106: providing calculations and values for predictability and significance. Displaying the available results and the interface allowing user for further adjustments to the alarms tunings).
In regards to claims (5 and 16), Srinivasan discloses wherein the alarm tuning recommendation data comprises predicted industrial operations metrics data associated with a predicted performance of the one or more industrial processes based on tuning of respective alarm configuration parameters for the one or more industrial processes, and the one or more programs further comprising instructions configured to: generate an interactive matrix display element comprising a matrix arrangement of the respective interactive display elements related to the one or more alarm identifiers based on the predicted industrial operations metrics data (see least para 100-103 can be presented to a user so that the user can review how one or more sets of alarm settings result in changes to the alarm counts).
In regards to claim 7, Srinivasan discloses the one or more programs further comprising instructions configured to: transmit one or more altered tuning values associated with the alarm tuning recommendation data to one or more controllers related to the one or more industrial processes (see the abstract and at least para 61, 67: the system allows the user to configure industrial process control with selected alarm settings. The system allows user to select and approve or not the proposed setting. The response of the user is sent to the controllers to set the options chosen by the user. If not approved by the user, engages in a what-if analysis that further provides other responses and options for the alarm tuning that the user can select and those selections are sent to be programed for the industrial processes).
In regards to claim 11, Srinivasan discloses the one or more programs further comprising instructions configured to: receive an acceptance indicator for an alarm tuning recommendation associated with the alarm tuning recommendation data via the interactive user interface; and transmit the acceptance indicator to the server system (see the abstract and at least para 61, 67: the system allows the user to configure industrial process control with selected alarm settings. The system allows user to select and approve or not the proposed setting. The response of the user is sent to the controllers to set the options chosen by the user. If not approved by the user, engages in a what-if analysis that further provides other responses and options for the alarm tuning that the user can select and those selections are sent to be programed for the industrial processes).
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 (i.e., changing from AIA to pre-AIA ) 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, 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) 6, 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan et a. (US 20180322770) as applied to claims above, in view of Law et al. (US 20180114414).
In regards to claims (6 and 17), Srinivasan teaches in response to an interaction with respect to the navigational interactive display element, alter the second user interface configuration for the interactive user interface to provide a third user interface configuration for the interactive user interface, and wherein the third user interface configuration provides an ability to alter respective alarm configuration parameters for the one or more industrial processes (see at least para 65-68, 71-78, 80-82, 103-106: providing calculations and values for predictability and significance. Displaying the available results and the interface allowing user for further adjustments to the alarms tunings).
Srinivasan doesn’t specifically teach the one or more programs further comprising instructions configured to: generate a navigational interactive display element comprising a real-time status of updates to the one or more alarm identifiers.
Law teaches the one or more programs further comprising instructions configured to: generate a navigational interactive display element comprising a real-time status of updates to the one or more alarm identifiers (see para 23 teaches “operate to control one or more industrial processes in real-time and in which an alarm handling and viewing system may be implemented to provide enhanced alarm handling”).
As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to use these teachings of Law in combination with the teachings of Srinivasan, for real-time status for the alarm data and identifiers, since it enhances the system in order to provide data as changes are applied.
Claim(s) 8-10, 18 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Srinivasan et a. (US 20180322770) as applied to claims above, in view of Cella et al. (US 20190171187).
In regards to claims (8 and 18), Srinivasan doesn’t specifically teach the one or more programs further comprising instructions configured to: in response to the request, interface with one or more machine learning models configured to generate at least a portion of the respective alarm count reduction predictions.
Cella teaches the one or more programs further comprising instructions configured to: in response to the request, interface with one or more machine learning models configured to generate at least a portion of the respective alarm count reduction predictions (see para 235: using machine learning and learning from decisions made on data and adapting and making data driven predictions).
As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to use these teachings of Cella in combination with the teachings of Srinivasan, for machine learning models to provide data and making data-driven predictions, since it enhances the system by adapting to the data associated to the required environment and provide improved resulting data (see para 235).
In regards to claim 9, Srinivasan doesn’t specifically teach the one or more programs further comprising instructions configured to: in response to the request, interface with the server system to generate at least a portion of the alarm tuning recommendation data based on an alarm philosophy rule set.
Cella teaches the one or more programs further comprising instructions configured to: in response to the request, interface with the server system to generate at least a portion of the alarm tuning recommendation data based on an alarm philosophy rule set (see para 235: using machine learning and learning from decisions made on data and adapting and making data driven predictions and providing data and results based on rule-based system).
As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to use these teachings of Cella in combination with the teachings of Srinivasan, for machine learning models to provide data and making data-driven results based on learned rule associated to the environment, since it enhances the system by adapting to the data associated to the required environment and provide improved resulting data (see para 235).
In regards to claims (10 and 19), Srinivasan teaches the one or more programs further comprising instructions configured to: receive a rejection indicator for an alarm tuning recommendation associated with the alarm tuning recommendation data (see para 61, 67: the system allows the user to approve or not the proposed setting if not approved engages in a what-if analysis that further provides other responses and options for the alarm tuning).
Srinivasan doesn’t specifically teach and provide updated training data associated with the rejection indicator to a machine learning model configured to provide the alarm insight data, wherein the machine learning model is configured learn from the rejection indicator to improve future alarm tuning recommendations.
Cella teaches and provide updated training data associated with the rejection indicator to a machine learning model configured to provide the alarm insight data, wherein the machine learning model is configured learn from the rejection indicator to improve future alarm tuning recommendations (see para 235: using machine learning and learning from decisions made on data and adapting and making data driven predictions and providing data and results based on rule-based system).
As such, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to use these teachings of Cella in combination with the teachings of Srinivasan, for using machine learning models to provide data and making data-driven results based on learned rule associated to the environment and use it with the responses to rejections as taught by Srinivasan, since it enhances the system by adapting to the data associated to the required environment and provide improved resulting data (see para 235).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARIO M VELEZ-LOPEZ whose telephone number is (571)270-7971. The examiner can normally be reached on M-F 10:30am-5:30pm EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Scott Baderman, can be reached at telephone number 571-272-3644. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MARIO M VELEZ-LOPEZ/
Examiner, Art Unit 2118
/SCOTT T BADERMAN/Supervisory Patent Examiner, Art Unit 2118
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