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：US20230016668A1

公开(公告)日：2023-01-19

申请号：US17954485

申请日：2022-09-28

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Ido Amihai ,  Moncef Chioua ,  Arzam Kotriwala ,  Martin Hollender ,  Dennis Janka ,  Felix Lenders ,  Jan Christoph Schlake ,  Benjamin Kloepper ,  Hadil Abukwaik

IPC: G05B13/02 ,  G06N3/08

Abstract: A method includes training a first control model by utilizing a first set of input data as first input, resulting in a trained first control model; copying the trained first control model to a second control model, wherein, after copying, the second input layer and the plurality of second hidden layers is identical to the plurality of first hidden layers, and the first output layer is replaced by the second output layer; freezing the plurality of second hidden layers; training the second control model by utilizing the first set of input data as second input, resulting in a trained second control model; and running the trained second control model by utilizing a second set of input data as second input, wherein the second output outputs the quality measure of the first control model.

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：US20200159732A1

公开(公告)日：2020-05-21

申请号：US16688622

申请日：2019-11-19

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Jeff Harding ,  Thomas Goldschmidt

IPC: G06F16/2455 ,  G06F16/21 ,  G06F16/242 ,  G06F16/248 ,  G06F16/23 ,  G06N5/04 ,  G06F16/2457 ,  G06F16/2458 ,  G06N20/00 ,  G06F16/25 ,  G06F16/29 ,  G06F8/36

Abstract: A system for reusing program code from a first completed application in a second under-development application based on identified patterns matching between the types of data accessed by the first and second applications. The system has an information model database, a pattern database, an API and applications which query the information model through the API, resulting in stored raw access data. The raw access data is extracted and patterns are generated based on similarity of the abstracted patterns as between the first and second applications. Application programmers access the pattern database to create new programs and implement prior computer code in the new program based on a pattern match on data accessed by a prior-developed application.

公开(公告)号：US11755605B2

公开(公告)日：2023-09-12

申请号：US17500972

申请日：2021-10-14

Applicant: ABB SCHWEIZ AG

Inventor： Benedikt Schmidt ,  Martin Hollender ,  Sylvia Maczey

IPC: G06F16/00 ,  G06F16/2458 ,  G06F16/23 ,  G06F16/2455 ,  G05B19/418

CPC classification number: G06F16/2477 ,  G05B19/4183 ,  G06F16/2379 ,  G06F16/24556

Abstract: A control module is adapted to control technical equipment by processing batch-run data from the technical equipment. The control module operates according to parameters that are obtained by a parameter module. The module receives a reference plurality of multi-variate reference time series with data values from sources that are related to the equipment. There are time series with measurement values and time series with data that describes particular manufacturing operations during a batch-run time interval. The module splits the time interval into phases by determining transitions between the particular manufacturing operations, and divides the time series into particular phase-specific partial series. For each phase separately, and for the phase-specific partial series in combination, the module differentiates phase-specific time series into relevant partial time series or non-relevant partial time series and set the parameters accordingly.

公开(公告)号：US20230019201A1

公开(公告)日：2023-01-19

申请号：US17956076

申请日：2022-09-29

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Ido Amihai ,  Arzam Muzaffar Kotriwala ,  Moncef Chioua ,  Dennis Janka ,  Felix Lenders ,  Jan Christoph Schlake ,  Martin Hollender ,  Hadil Abukwaik ,  Benjamin Kloepper

IPC: G05B13/02

Abstract: An industrial plant machine learning system includes a machine learning model, providing machine learning data, an industrial plant providing plant data and an abstraction layer, connecting the machine learning model and the industrial plant, wherein the abstraction layer is configured to provide standardized communication between the machine learning model and the industrial plant, using a machine learning markup language.

公开(公告)号：US11237804B2

公开(公告)日：2022-02-01

申请号：US16688622

申请日：2019-11-19

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Jeff Harding ,  Thomas Goldschmidt

IPC: G06F16/21 ,  G06F16/23 ,  G06F16/242 ,  G06F16/2455 ,  G06F16/2457 ,  G06F16/2458 ,  G06F16/248 ,  G06F16/25 ,  G06F16/29 ,  G06F16/93 ,  G06F40/279 ,  G06F8/36 ,  G06N20/00 ,  G06N5/04

Abstract: A system for reusing program code from a first completed application in a second under-development application based on identified patterns matching between the types of data accessed by the first and second applications. The system has an information model database, a pattern database, an API and applications which query the information model through the API, resulting in stored raw access data. The raw access data is extracted and patterns are generated based on similarity of the abstracted patterns as between the first and second applications. Application programmers access the pattern database to create new programs and implement prior computer code in the new program based on a pattern match on data accessed by a prior-developed application.

公开(公告)号：US20220019209A1

公开(公告)日：2022-01-20

申请号：US17489882

申请日：2021-09-30

Applicant: ABB Schweiz AG

Inventor： Benjamin Kloepper ,  Jan-Christoph Schlake ,  Benedikt Schmidt ,  Bernhard Wullt ,  Anton Ronquist

IPC: G05B23/02

Abstract: An asset condition monitoring method with automatic anomaly detection may include receiving local condition data from an asset fleet, identifying at least one anomaly in the received condition data, identifying a new potential failure case dependent on the identified anomaly, determining a specific condition model dependent on the identified new potential failure case, where the specific condition model is configured for predicting the new potential failure case, and providing the specific condition model to the plurality of assets and/or to digital models of the plurality of assets.

公开(公告)号：US20200333773A1

公开(公告)日：2020-10-22

申请号：US16850010

申请日：2020-04-16

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Martin Hollender ,  Felix Lenders

IPC: G05B19/418

Abstract: A computer-implemented method to control technical equipment that performs a production batch-run of a production process, the technical equipment providing data in a form of time-series from a set of data sources, the data sources being related to the technical equipment, includes: accessing a reference time-series with data from a previously performed batch-run of the production process, the reference time-series being related to a parameter for the technical equipment; and while the technical equipment performs the production batch-run: receiving a production time-series with data, identifying a sub-series of the reference time-series, and comparing the received time-series and the sub-series of the reference time-series, to provide an indication of similarity or non-similarity, in case of similarity, controlling the technical equipment during a continuation of the production batch-run, by using the parameter as control parameter.

公开(公告)号：US20190294998A1

公开(公告)日：2019-09-26

申请号：US16441028

申请日：2019-06-14

Applicant: ABB Schweiz AG

Inventor： Benjamin Kloepper ,  Benedikt Schmidt ,  Mohamed-Zied Ouertani

IPC: G06N20/00

Abstract: A computer system can be configured to: receive, in a low-precision mode, first status data generated by one or more sensors, the first status data reflecting technical parameters of a technical system, the first status data exhibiting a first precision level; apply a low-precision machine learning model to analyze the first status data for one or more indicators of an abnormal technical status, the machine learning model having been trained with data exhibiting the first precision level; send, based on an abnormal technical status being indicated, instructions for the one or more sensors to generate second status data exhibiting a second precision level, the second precision level being associated with greater accuracy than the first precision level; receive the second status data exhibiting the second precision level based on the sent instructions; providing the second status data to a data analyzer.