公开(公告)号：US20230384752A1

公开(公告)日：2023-11-30

申请号：US18448523

申请日：2023-08-11

Applicant: ABB Schweiz AG

Inventor： Pablo Rodriguez ,  Jens Doppelhamer ,  Benjamin Kloepper ,  Reuben Borrison ,  Marcel Dix ,  Benedikt Schmidt ,  Hadil Abukwaik ,  Arzam Muzaffar Kotriwala ,  Sylvia Maczey ,  Dawid Ziobro ,  Simon Hallstadius Linge ,  Marco Gaertler ,  Divyasheel Sharma ,  Chandrika K R ,  Gayathri Gopalakrishnan ,  Matthias Berning ,  Roland Braun

IPC: G05B19/05

CPC classification number: G05B19/056 ,  G05B2219/1204

Abstract: A method includes acquiring state variables that characterize an operational state of an industrial plant; acquiring interaction events of a plant operator interacting with the distributed control system via a human-machine interface; determining based on the interaction events, and with state variables as input data, whether one or more interaction events are indicative of the plant operator executing a task that is not sufficiently covered by engineering of the distributed control system. When this determination is positive, mapping the input data to an amendment and/or augmentation for the engineering tool that has generated the application code.

公开(公告)号：US20230050321A1

公开(公告)日：2023-02-16

申请号：US17977355

申请日：2022-10-31

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Marcel Dix ,  Martin Hollender ,  Andrew Cohen ,  Arzam Muzaffar Kotriwala ,  Marco Gaertler ,  Sylvia Maczey ,  Benjamin Kloepper

IPC: G05B19/042

Abstract: A method for generating a process model modeling a manual mode procedure instance of a plant process includes providing log events of operational actions; selecting related sequences of manual mode operational actions from the log events; filtering the related sequences according to an individual plant section; identifying a sequential order from the filtered related sequences; determining statistical properties of values of related process variables and/or statistical properties of values of related set point changes to each sequential ordered manual mode operational action from the filtered related sequences; generating the process model of the manual mode procedure instance by arranging related manual mode operational actions with the sequential order of each operational action assigned with the statistical properties of the values of related process variables and/or assigned with the statistical properties of the values of the related set point changes.

公开(公告)号：US20240019849A1

公开(公告)日：2024-01-18

申请号：US18475681

申请日：2023-09-27

Applicant: ABB Schweiz AG

Inventor： Dawid Ziobro ,  Arzam Muzaffar Kotriwala ,  Marco Gaertler ,  Jens Doppelhamer ,  Pablo Rodriguez ,  Matthias Berning ,  Benjamin Kloepper ,  Reuben Borrison ,  Marcel Dix ,  Benedikt Schmidt ,  Hadil Abukwaik ,  Sylvia Maczey ,  Simon Hallstadius Linge ,  Divyasheel Sharma ,  Chandrika K R ,  Gayathri Gopalakrishnan

IPC: G05B19/418

CPC classification number: G05B19/4184 ,  G05B2219/34465

Abstract: An assistance system comprises a plant topology repository comprising a representation of the components of the plant and relations between the components; a monitoring subsystem configured for monitoring signals from the components and for monitoring a related event, as a key for the monitored signals; an aggregation subsystem configured for storing a plurality of the monitored signals and the related events, wherein at least one of the events is the abnormal situation; an identification subsystem configured for comparing currently monitored signals to stored monitored signals and the related event; and an evaluation subsystem configured for outputting a predefined action, if the currently monitored signals match to the event that is the abnormal situation.

公开(公告)号：US20220343193A1

公开(公告)日：2022-10-27

申请号：US17724693

申请日：2022-04-20

Applicant: ABB Schweiz AG

Inventor： Divyasheel Sharma ,  Benjamin Kloepper ,  Marco Gaertler ,  Dawid Ziobro ,  Simon Linge ,  Pablo Rodriguez ,  Matthias Berning ,  Reuben Borrison ,  Marcel Dix ,  Benedikt Schmidt ,  Hadil Abukwaik ,  Arzam Muzaffar Kotriwala ,  Sylvia Maczey ,  Jens Doppelhamer ,  Chandrika K R ,  Gayathri Gopalakrishnan

IPC: G06N5/04

Abstract: A decision support system and method for an industrial plant is configured and operates to: obtain a causal graph modeling causal assumptions relating to conditional dependence between variables in the industrial plant; obtain observational data relating to operation of the industrial plant; and perform causal inference using the causal graph and the observational data to estimate at least one causal effect relevant for making decisions when operating the industrial plant.

公开(公告)号：US12147222B2

公开(公告)日：2024-11-19

申请号：US17500982

申请日：2021-10-14

Applicant: ABB Schweiz AG

Inventor： Reinhard Bauer ,  Martin Hollender ,  Marco Gaertler

IPC: G05B19/418

Abstract: To determine a quality indicator of production batch-run of a production process, a computer compares time-series with multi-source data from a reference batch-run and time-series with multi-source data from the production batch-run. Before comparing, the computer converts multi-variate time-series to uni-variate time-series, by first multiplying data values of source-specific uni-variate time-series with source-specific factors from a conversion factor vector and second summing up the multiplied data values according to discrete time points. The source-specific factors of the conversion factor vector are obtained earlier by processing reference data, including the determination of characteristic portions of the time-series, converting, aligning by time-warping and evaluating displacement in time between characteristic portions before alignment and after alignment.

公开(公告)号：US20240005232A1

公开(公告)日：2024-01-04

申请号：US18448535

申请日：2023-08-11

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Jens Doppelhamer ,  Pablo Rodriguez ,  Benjamin Kloepper ,  Reuben Borrison ,  Marcel Dix ,  Hadil Abukwaik ,  Arzam Muzaffar Kotriwala ,  Sylvia Maczey ,  Dawid Ziobro ,  Simon Hallstadius Linge ,  Marco Gaertler ,  Divyasheel Sharma ,  Chandrika K R ,  Gayathri Gopalakrishnan ,  Matthias Berning

IPC: G06Q10/0631

CPC classification number: G06Q10/063112 ,  G06Q10/06312

Abstract: A method for generating and/or augmenting an execution protocol for an SOP in an industrial plant includes providing at least one SOP of the plant, which includes a plurality of steps; providing measurement data; for each step of the SOP, determining from the measurement data a subset of the measurement data that is indicative of actions performed for the purpose of executing this particular step of the SOP; and aggregating the subset of the measurement data determined for each step of the SOP into at least one instruction for executing this particular step of the SOP, wherein this instruction is part of the sought protocol.

公开(公告)号：US20230074570A1

公开(公告)日：2023-03-09

申请号：US17899856

申请日：2022-08-31

Applicant: ABB Schweiz AG

Inventor： Andrea Macauda ,  Raja Sivalingam ,  Chandrika K R ,  Matthias Berning ,  Dawid Ziobro ,  Sylvia Maczey ,  Pablo Rodriquez ,  Benjamin Kloepper ,  Reuben Borrison ,  Marcel Dix ,  Benedikt Schmidt ,  Hadil Abukwaik ,  Arzam Muzaffar Kotriwala ,  Divyasheel Sharma ,  Gayathri Gopalakrishnan ,  Simon Linge ,  Marco Gaertler ,  Jens Doppelhamer

IPC: G05B23/02

Abstract: An industrial plant operator intervention system for use in an industrial plant includes a processing unit configured to monitor and analyze industrial plant operation data to detect an anomaly in the industrial plant operation data that warrants initiating an operator intervention, and in response to detecting the anomaly, automatically determine a user interface configuration of a user interface to be presented to a designated operator who is to perform the operator intervention. The user interface configuration is determined on the basis of technical context data, including industrial plant operation data associated with the anomaly, and on the basis of operator data pertaining to the designated operator, in such a manner that an anomaly-related and operator-specific user interface configuration is obtained.

公开(公告)号：US20220035351A1

公开(公告)日：2022-02-03

申请号：US17500982

申请日：2021-10-14

Applicant: ABB Schweiz AG

Inventor： Reinhard Bauer ,  Martin Hollender ,  Marco Gaertler

IPC: G05B19/418

Abstract: To determine a quality indicator of production batch-run of a production process, a computer compares time-series with multi-source data from a reference batch-run and time-series with multi-source data from the production batch-run. Before comparing, the computer converts multi-variate time-series to uni-variate time-series, by first multiplying data values of source-specific uni-variate time-series with source-specific factors from a conversion factor vector and second summing up the multiplied data values according to discrete time points. The source-specific factors of the conversion factor vector are obtained earlier by processing reference data, including the determination of characteristic portions of the time-series, converting, aligning by time-warping and evaluating displacement in time between characteristic portions before alignment and after alignment.

公开(公告)号：US20240160160A1

公开(公告)日：2024-05-16

申请号：US18455340

申请日：2023-08-24

Applicant: ABB Schweiz AG

Inventor： Ruomu Tan ,  Marco Gaertler ,  Benjamin Kloepper ,  Sylvia Maczey ,  Andreas Potschka ,  Martin Hollender ,  Benedikt Schmidt

IPC: G05B13/02

CPC classification number: G05B13/027

Abstract: A method for detecting change points, CPs, in a signal of a process automation system, includes, in an offline learning phase, unsupervised, candidate CPs on at least one offline signal using unsupervised detection method are detected, CPs are selected from the candidate CPs; the selected CPs are provided to a supervised process; in the supervised process, an offline machine-learning (ML) system is trained to refine CPs from the selected CPs using a supervised machine learning method; a training data set for an online ML system is created using the offline ML system by projecting the refined CPs on the signal; the online ML system is trained in a supervised manner, using the created training data set; and after the offline learning phase, CPs are detected using the trained online ML system.

公开(公告)号：US20230393538A1

公开(公告)日：2023-12-07

申请号：US18452313

申请日：2023-08-18

Applicant: ABB Schweiz AG

Inventor： Dawid Ziobro ,  Jens Doppelhamer ,  Benedikt Schmidt ,  Simon Hallstadius Linge ,  Gayathri Gopalakrishnan ,  Pablo Rodriguez ,  Benjamin Kloepper ,  Reuben Borrison ,  Marcel Dix ,  Hadil Abukwaik ,  Arzam Muzaffar Kotriwala ,  Sylvia Maczey ,  Marco Gaertler ,  Divyasheel Sharma ,  Chandrika K R ,  Matthias Berning

IPC: G05B13/02 ,  G05B23/02

CPC classification number: G05B13/0265 ,  G05B23/0216 ,  G05B2223/02

Abstract: A method for providing a solution strategy for a current event in industrial process automation includes monitoring a process for events and recording manual user action data, upon occurrence of an event, acquiring the recorded data regarding manual user actions before, during, and after the occurrence of the event, learning a procedure for handling the event based on the acquired data, and applying the learnt procedure to a currently occurring event.