公开(公告)号：US20240394633A1

公开(公告)日：2024-11-28

申请号：US18672552

申请日：2024-05-23

Applicant: ABB Schweiz AG

Inventor： Georg Gutermuth ,  Bernhard Primas ,  Matthias Biskoping ,  Matthias Schloeder ,  Arzam Muzaffar Kotriwala

IPC: G06Q10/0633 ,  G06Q50/04

Abstract: A computer-implemented method for a plant operation optimization component includes determining optimal operation set points and, based on optimal operation set points and corresponding operational costs, providing output allowing for selecting a tariff.

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：US20230029400A1

公开(公告)日：2023-01-26

申请号：US17957609

申请日：2022-09-30

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: G06N20/00

Abstract: A method of hierarchical machine learning includes receiving a topology model having information on hierarchical relations between components of the industrial plant, determining a representation hierarchy comprising a plurality of levels, wherein each representation on a higher level represents a group of representations on a lower level, wherein the representations comprise a machine learning model, and training an output machine learning model using the determined hierarchical representations.

公开(公告)号：US20230019404A1

公开(公告)日：2023-01-19

申请号：US17956117

申请日：2022-09-29

Applicant: ABB Schweiz AG

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

IPC: G06N20/20

Abstract: A computer-implemented method for automating the development of industrial machine learning applications includes one or more sub-methods that, depending on the industrial machine learning problem, may be executed iteratively. These sub-methods include at least one of a method to automate the data cleaning in training and later application of machine learning models, a method to label time series (in particular signal data) with help of other timestamp records, feature engineering with the help of process mining, and automated hyper-parameter tuning for data segmentation and classification.

公开(公告)号：US20250085682A1

公开(公告)日：2025-03-13

申请号：US18827992

申请日：2024-09-09

Applicant: ABB Schweiz AG

Inventor： Arzam Muzaffar Kotriwala ,  Bernhard Primas ,  Ido Amihai ,  Georg Gutermuth ,  Matthias Schloeder ,  Matthias Biskoping

IPC: G05B19/042

Abstract: A system for optimizing an energy management of a site, comprising: an energy optimizer, wherein the energy optimizer determines one or more optimization goals based on an optimization algorithm, a data variator adapted to provide at least one first energy data input and at least one second energy data input, different to the first energy data input, to the energy optimizer, wherein the energy optimizer receives the first and second energy data inputs from the data variator, and to determine, based the first and second energy data inputs, respective at least one first and second energy data outputs via the optimization algorithm, wherein a data sensitivity of the energy optimizer is determined with respect to the first and second energy data inputs and the first and second energy data outputs.

公开(公告)号：US20250053885A1

公开(公告)日：2025-02-13

申请号：US18928402

申请日：2024-10-28

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Benjamin Kloepper ,  Arzam Muzaffar Kotriwala ,  Yemao Man ,  Dawid Ziobro ,  Gayathri Gopalakrishnan ,  Joakim Astrom ,  Marcel Dix ,  Divyasheel Sharma

IPC: G06N20/20

Abstract: A method for explanation of machine learning results based on using a model collection includes training at least two machine learning models with at least two competing strategies for the at least one dataset; and using the least two machine learning models to yield at least two different predictions and/or at least two explanations for the at least one dataset.

公开(公告)号：US20240302832A1

公开(公告)日：2024-09-12

申请号：US18668370

申请日：2024-05-20

Applicant: ABB Schweiz AG

Inventor： Hadil Abukwaik ,  Divyasheel Sharma ,  Benjamin Kloepper ,  Arzam Muzaffar Kotriwala ,  Pablo Rodriguez ,  Benedikt Schmidt ,  Ruomu Tan ,  Chandrika K R ,  Reuben Borrison ,  Marcel Dix ,  Jens Doppelhamer

IPC: G05B23/02

CPC classification number: G05B23/0254 ,  G05B23/027 ,  G05B23/0286

Abstract: A method for training a prediction model includes obtaining training samples representing states of the process that do not cause the undesired event; obtaining based on a process model and a set of predetermined rules that stipulate states having an increased likelihood of the undesired event occurring; training samples representing states with an increased likelihood to cause the undesired event; providing samples to the to-be-trained prediction model to obtain a prediction of the likelihood for occurrence of the undesired event in a state of the process represented by the respective sample; rating a difference between the prediction and the label of the respective sample using a predetermined loss function; and optimizing parameters such that, when predictions are made, the rating by the loss function improves.

公开(公告)号：US11835429B2

公开(公告)日：2023-12-05

申请号：US17480163

申请日：2021-09-21

Applicant: ABB Schweiz AG

Inventor： Moncef Chioua ,  Subanatarajan Subbiah ,  Arzam Muzaffar Kotriwala ,  Ido Amihai

IPC: G06F11/30 ,  G01M99/00

CPC classification number: G01M99/005

Abstract: An apparatus for equipment monitoring includes an input unit, a processing unit, and an output unit. The input unit is configured to provide the processing unit with batches of temporal sensor data for an item of equipment. Each batch of temporal sensor data includes temporal sensor values as a function of time. The processing unit is configured to process the batches of temporal sensor data to determine batches of spectral sensor data. Each batch of spectral sensor data includes spectral sensor values as a function of frequency. The processing unit is configured to implement at least one statistical process algorithm to process the spectral sensor values for the batches of spectral sensor data to determine index values. For each batch of spectral sensor data there is an index value determined by each of the statistical process algorithms.

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.