CTNF 18/616,621 CTNF 94264 DETAILED ACTION Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claim Objections 07-29-01 AIA Claim 1 is objected to because of the following informalities: Claim 1 recites “selecting by the pre-trained rule engine at least one data from historic data expert opinion data and equipment standard data …” that has typo. Should be “selecting by the pre-trained rule engine at least one data from historic data, expert opinion data and equipment standard data …”. Claim 11 recites “receive information related to at least one equipment” that has typo. Should be “receive real-time information related to at least one equipment”. Claim 12 recites “wherein the information indicates at least one of current operation status of the at least one equipment” that has typo. Should be “wherein the real-time information indicates at least one of current operation status of the at least one equipment” . Appropriate correction is required. Claim Rejections - 35 USC § 103 07-20-aia AIA 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. 07-21-aia AIA Claim s 1-3, 5-6, 11-13 and 15-16 are rejected under 35 U.S.C. 103 as being unpatentable over Eryurek US 20050197803 A1 in view of GUPTA EP 3599527 A1 . Regarding claim 11, Eryurek teaches a pre-trained rule engine for providing an assistance to correct at least one abnormal event encountered for at least one equipment in an industrial environment (Figs. 1-2 & 37 [0072] [0179] [0183] rules engine 290 a client system), the pre-trained rule engine comprising: a processor; and a memory communicatively coupled to the processor; wherein the memory stores processor-executable instructions, which, on execution, cause the processor to (Fig. 1 [0072] computer system): Receive real-time information related to at least one equipment, in an industrial environment, upon identification of an at least one abnormal event encountered for the at least one equipment (Figs. 2 & 37 [0081] [0179] [0183] SPM blocks within the devices detect SPM conditions i.e. “upon identification of an at least one abnormal event encountered for the at least one equipment”, then these abnormal conditions are sent to the rules engine 290 along with the statistical monitoring data collected by these filed device i.e. “receive real-time information related to at least one equipment”); select at least one data from historic data ([0179] rules engine 290 receives historical data) and expert opinion data ([0179] a set of rules 292) associated with the at least one equipment, based on real-time state information, from the real-time information, related to the at least one equipment (Fig. 38 [0180] [0182] [0187] [0188] apply matched rules based on the SPM data and the abnormal conditions received from the SPM blocks to determine the abnormalities and the actions to take); analyze the received information using the selected at least one data (Fig. 38 [0180] [0187] [0188] apply rules based on the SPM data and the abnormal conditions received from the SPM blocks to determine the abnormalities and the actions to take); generate an assistance for correcting the at least one abnormal event encountered for the at least one equipment based on the analysis (Fig. 38 [0180] [0187] [0188] apply rules based on the SPM data and the abnormal conditions received from the SPM blocks to determine the abnormalities and the actions to take); and provide the assistance to an operator for correcting the at least one abnormal event encountered for the at least one equipment (Fig. 42 [0196] alarm display includes corrective actions). Eryurek does not explicitly further teach selecting at least one data from equipment standard data associated with the at least one equipment. GUPTA explicitly teaches in an analogous art that equipment standard data ([0054] [0075] process interlocks and closed loop) associated with the at least one equipment. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Eryurek to incorporate the teachings of GUPTA, because they all directed to abnormal event detection and/or correction, to make the rule engine wherein selecting at least one data from equipment standard data associated with the at least one equipment. One of ordinary skill in the art would have been motivated to do this modification so as to determining a corrective action for the predicted abnormal condition associated with the equipment, as GUPTA teaches in abstract. Regarding claim 1, it is directed to a method of carrying out the rule engine with similar limitations as set forth in claim 11. Since Eryurek and GUPTA teach the claimed rule engine, they teach the method steps for implementing the rule engine. Regarding claims 2 and 12, Eryurek further teaches the real-time information indicates at least one of current operation status of the at least one equipment (Figs. 2 & 37 [0081] [0179] [0183] SPM blocks within the devices detect SPM conditions), real-time state information related to the at least one equipment (Figs. 2 & 37 [0081] [0179] [0183] SPM blocks within the devices detect SPM conditions), one or more categories of sub-equipment associated with the at least one equipment (Figs. 2 & 37 [0081] [0179] [0183] SPM blocks within the devices i.e. “sub-equipment” detect SPM conditions), one or more alarm conditions (Figs. 2 & 37 [0081] [0179] [0183] SPM blocks within the devices detect SPM conditions), and one or more sub-equipment operation status (Figs. 2 & 37 [0081] [0179] [0183] SPM blocks within the devices i.e. “sub-equipment” detect SPM conditions). Regarding claims 3 and 13, Eryurek further teaches the pre-trained rule engine is trained using the historic data, the expert opinion data and the equipment standard data ([0134] [0146] [0151] the trained regression model, neural network model based on the collected data are used by the rule engine). Regarding claims 5 and 15, Eryurek further teaches the expert opinion data comprises one or more industrial expert opinions associated with correcting each of one or more abnormal events encountered for the at least one equipment (Fig. 38 [0184] - [0187] user defined rules with corrective actions). Regarding claims 6 and 16, GUPTA further teaches the equipment standard data comprises Original Equipment Manufacturer (OEM) data specification received from manufacturer of the at least one equipment (Table 3 equipment list with OEM specifications). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Eryurek to incorporate the teachings of GUPTA, because they all directed to abnormal event detection and/or correction, to make the rule engine/method wherein the equipment standard data comprises Original Equipment Manufacturer (OEM) data specification received from manufacturer of the at least one equipment. One of ordinary skill in the art would have been motivated to do this modification so as to determining a corrective action for the predicted abnormal condition associated with the equipment, as GUPTA teaches in abstract . 07-21-aia AIA Claim s 4, 10, 14 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Eryurek in view of GUPTA as applied to claims above 1-3, 5-6, 11-13 and 15-16, further in view of NIEMIEC US 20190129395 A1 . Regarding claims 4 and 14, neither Eryurek nor GUPTA explicitly further teaches the historic data comprises plurality of operator actions performed by one or more operators to correct each of one or more abnormal events previously occurred for the at least one equipment. NIEMIEC explicitly teaches in an analogous art that the historic data comprises plurality of operator actions performed by one or more operators to correct each of one or more abnormal events previously occurred for the at least one equipment ([0035] [0036] [0058] operator action history corresponding to alarm data). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Eryurek and GUPTA to incorporate the teachings of NIEMIEC, because they all directed to abnormal event detection and/or correction, to make the rule engine/method wherein the historic data comprises plurality of operator actions performed by one or more operators to correct each of one or more abnormal events previously occurred for the at least one equipment. One of ordinary skill in the art would have been motivated to do this modification so as to guide the operator's action in response to the alarm, as NIEMIEC teaches in [0036]. Regarding claims 10 and 20, NIEMIEC further teaches fine-tune the pre-trained rule engine based on real-time operator actions performed on the at least one equipment to correct the at least one abnormal event ([0035] [0036] using operator action data to derive relationship models between the alarm events and operator action and or KPI data and operator actions, the relationship models later on can be used to guide the operator’s action in response to the alarm). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Eryurek and GUPTA to incorporate the teachings of NIEMIEC, because they all directed to abnormal event detection and/or correction, to make the rule engine/method wherein fine-tune the pre-trained rule engine based on real-time operator actions performed on the at least one equipment to correct the at least one abnormal event. One of ordinary skill in the art would have been motivated to do this modification so as to guide the operator's action in response to the alarm, as NIEMIEC teaches in [0036] . 07-21-aia AIA Claim s 7 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Eryurek in view of GUPTA as applied to claims above 1-3, 5-6, 11-13 and 15-16, further in view of Cozma US 20220318115 A1 . Regarding claims 7 and 17, Eryurek further teaches the assistance comprises at least one of text-based assistance (Fig. 42 [0196] message assistance with text), value-based assistance comprising face plates and graphical elements (Fig. 43 386 and 385), graph-based assistance (Fig. 43 385), notification-based assistance (Fig. 42 Alarm and message), and message-based assistance (Fig. 42 [0196] message assistance with text). Neither Eryurek nor GUPTA explicitly further teaches the assistance comprises at least one of email-based assistance. Cozma explicitly teaches in an analogous art that the assistance comprises at least one of email-based assistance ([0084] alert notification such as email message). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Eryurek and GUPTA to incorporate the teachings of Cozma, because they all directed to abnormal event detection and/or correction, to make the rule engine/method wherein the assistance comprises at least one of email-based assistance. One of ordinary skill in the art would have been motivated to do this modification so as to notify a user a critical severity level alert, as Cozma teaches in [0096] . 07-21-aia AIA Claim s 9 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Eryurek in view of GUPTA as applied to claims above 1-3, 5-6, 11-13 and 15-16, further in view of NIEMIEC and Gugaliya US 20200132773 A1 . Regarding calims 9 and 19, neither Eryurek nor GUPTA explicitly further teaches checking for previous occurrence of the at least one abnormal event to be greater than a predefined number of times in the historic data. Gugaliya explicitly teaches in an analogous art that checking for previous occurrence of the at least one abnormal event to be greater than a predefined number of times in the historic data ([0014] the number of abnormal operating instances identified during the time period is greater than a threshold); and NIEMIEC further teaches identifying one or more operator actions performed for the previously occurrences of the at least one abnormal event, to generate the assistance for correcting the at least one abnormal event ([0035] [0036] [0058] identifying other operator actions that handled the previous alarm event and show them to current operator). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified Eryurek and GUPTA to incorporate the teachings of NIEMIEC and Gugaliya, because they all directed to abnormal event detection and/or correction, to make the rule engine/method wherein checking for previous occurrence of the at least one abnormal event to be greater than a predefined number of times in the historic data; and identifying one or more operator actions performed for the previously occurrences of the at least one abnormal event, to generate the assistance for correcting the at least one abnormal event.. One of ordinary skill in the art would have been motivated to do this modification so as to guide the operator's action in response to the alarm, as NIEMIEC teaches in [0036] . Allowable Subject Matter Claims 8 and 18 are objected to as being dependent upon rejected base claims, but would be allowable if rewritten to overcome the objections set forth in this Office action and in independent form including all of the limitations of the base claim and any intervening claims. 13-03-01 AIA The following is a statement of reasons for the indication of allowable subject matter: Claims 8 and 18 depends on claims 1 and 11, respectively, Eryurek and GUPTA together teach the claim limitations of claims 1 and 11. Cozma teaches identifying priority factor related to the at least one abnormal event encountered for the at least one equipment based on the real-time state information ([0044] defining severity level of the alert). However, Eryurek, GUPTA and Cozma do not teach or suggest individually or in combination: selecting the at least one data from the historic data, the expert opinion data and the equipment standard data based on the identified priority factor . Conclusion 07-96 AIA The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Redmond US 20210088369 A1 teaches correction for anomalies for blockage event in industrial system. Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael Tang whose telephone number is (571)272-7437. The examiner can normally be reached M-F 7:30-4 EST. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamini Shah can be reached on (571)272-2279. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. 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If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /M.T./ Examiner, Art Unit 2115 /KAMINI S SHAH/ Supervisory Patent Examiner, Art Unit 2115 Application/Control Number: 18/616,621 Page 2 Art Unit: 2115 Application/Control Number: 18/616,621 Page 3 Art Unit: 2115 Application/Control Number: 18/616,621 Page 4 Art Unit: 2115 Application/Control Number: 18/616,621 Page 5 Art Unit: 2115 Application/Control Number: 18/616,621 Page 6 Art Unit: 2115 Application/Control Number: 18/616,621 Page 7 Art Unit: 2115 Application/Control Number: 18/616,621 Page 8 Art Unit: 2115 Application/Control Number: 18/616,621 Page 9 Art Unit: 2115 Application/Control Number: 18/616,621 Page 10 Art Unit: 2115 Application/Control Number: 18/616,621 Page 11 Art Unit: 2115 Application/Control Number: 18/616,621 Page 12 Art Unit: 2115 Application/Control Number: 18/616,621 Page 13 Art Unit: 2115
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