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：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：US20240301575A1

公开(公告)日：2024-09-12

申请号：US18667600

申请日：2024-05-17

Applicant: ABB Schweiz AG

Inventor： Matthias Biskoping ,  Georg Gutermuth ,  Felix Lenders ,  Bernhard Primas ,  Kai Koenig

IPC: C25B15/02 ,  C25B1/04 ,  C25B9/70

CPC classification number: C25B15/02 ,  C25B1/04 ,  C25B9/70

Abstract: A method for producing hydrogen using two types of electrolysis systems, the first having an active DC module and at least one first-type electrolyzer producing a first hydrogen output by using a first power from the active DC module, and the second electrolysis system having a passive DC module and at least one second-type electrolyzer producing a second hydrogen output by using a second power from the passive DC module. The method includes increasing the first hydrogen output and when it crosses a first predefined hydrogen output threshold, switching on the second electrolysis system and decreasing the first hydrogen output of the first electrolysis system to the first predefined hydrogen output threshold minus the second hydrogen output, so that an overall hydrogen output of the hydrogen production plant is a sum of the first hydrogen output and the second hydrogen output.

公开(公告)号：US20240168467A1

公开(公告)日：2024-05-23

申请号：US18549428

申请日：2021-03-12

Applicant: ABB Schweiz AG

Inventor： Arzam Kotriwala ,  Nuo Li ,  Jan-Christoph Schlake ,  Prerna Juhlin ,  Felix Lenders ,  Matthias Biskoping ,  Benjamin Kloepper ,  Kalpesh Bhalodi ,  Andreas Potschka ,  Dennis Janka

IPC: G05B19/418

CPC classification number: G05B19/41875 ,  G05B2219/32368

Abstract: A computer-implemented method is provided. The method includes receiving geological data of a material and processing data referring to a plurality of processing stations of an industrial process for manufacturing a product from the material; receiving, for the geological data and the processing data, corresponding product quality data of the manufactured product; and training or retraining a prediction model for the industrial process to determine predicted product quality data for the geological data and the processing data

公开(公告)号：US20230094914A1

公开(公告)日：2023-03-30

申请号：US17956097

申请日：2022-09-29

Applicant: ABB Schweiz AG

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

IPC: G06N20/00

Abstract: A computer-implemented method of generating a training data set for training an artificial intelligence module includes providing first and second data sets, the first data set including first data elements indicative of a first operational condition, the second data set including second data elements indicative of a second operational condition that matches the first operational condition. The method further comprises determining a data transformation for transforming the first data elements into the second data elements; applying the data transformation to the first data elements and/or to further data elements of further data sets, thereby generating a transformed data set; and generating a training data set for training the AI module based on at least a part of the transformed data set.

公开(公告)号：US20240370004A1

公开(公告)日：2024-11-07

申请号：US18772777

申请日：2024-07-15

Applicant: ABB Schweiz AG

Inventor： Georg Gutermuth ,  Matthias Biskoping ,  Felix Lenders

IPC: G05B19/418

Abstract: A method for controlling operation of an electrolyzer plant includes using a first model to determine first operating points for a first period of time; using a second model to simulate operation of the electrolyzer plant for the first operating points for a second period of time that is shorter than and comprised in the first period of time, the second model being a model having higher prediction accuracy for the operation of the electrolyzer plant than the first model, and determining whether the simulated operation meets a predetermined requirement. Upon determining that the simulated operation does not meet the predetermined requirement, adjusting one or more parameters and/or one or more boundary conditions of the first model, and upon determining that the simulated operation meets the predetermined requirement, setting the first operating points as target operating points for the predetermined second period of time.

公开(公告)号：US20240069518A1

公开(公告)日：2024-02-29

申请号：US18259799

申请日：2020-12-30

Applicant: ABB Schweiz AG

Inventor： Prerna Juhlin ,  Arzam Muzaffar Kotriwala ,  Nuo Li ,  Jan-Christoph Schlake ,  Felix Lenders ,  Matthias Biskoping ,  Benjamin Kloepper ,  Kalpesh Bhalodi ,  Andreas Potschka ,  Dennis Janka

IPC: G05B19/406

CPC classification number: G05B19/406 ,  G05B2219/31449

Abstract: A method for monitoring a continuous industrial process is described. The industrial process includes a number of processing stations for processing material and a material flow between the number of processing stations. Each processing station dynamically provides data representing a state of the processing station. The method includes providing, for each processing station, a processing station layout of the processing station. The method further includes providing, for each processing station, an interface model of the processing station. The method further includes generating an information metamodel from the processing station layout and the interface model of the number of processing stations. The method further includes generating an adaptive simulation model of the industrial process by importing the data representing the state of the processing station provided by the number of processing stations into the adaptive simulation model via the information metamodel.

公开(公告)号：US20230236563A1

公开(公告)日：2023-07-27

申请号：US18193863

申请日：2023-03-31

Applicant: ABB Schweiz AG

Inventor： Felix Lenders ,  Georg Gutermuth ,  Bernhard Primas

IPC: G05B19/042

CPC classification number: G05B19/042 ,  G05B2219/2639

Abstract: A method for evaluating an energy efficiency of a second energy consumption scenario of a site includes obtaining a first energy consumption scenario, which comprises a first time-series of energy consumption data of at least one device, and a quality measure of the first energy consumption scenario; obtaining the second energy consumption scenario, which comprises a second time-series of energy consumption data, wherein the second energy consumption scenario has a same or a shorter duration than the first energy consumption scenario; comparing the second time-series of energy consumption data to the first time-series of energy consumption data; and if or when the second time-series of energy consumption data is similar to the first time-series of energy consumption data, outputting the quality measure of the first energy consumption scenario.

公开(公告)号：US20230023896A1

公开(公告)日：2023-01-26

申请号：US17957592

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: G05B19/418 ,  G06N20/00

Abstract: A method of transfer learning for a specific production process of an industrial plant includes providing data templates defining expected data for a production process, and providing plant data, wherein the data templates define groupings for the expected data according to their relation in the industrial plant; determining a process instance and defining a mapping with the plant data; determining historic process data; determining training data using the determined process instance and the determined historic process data, wherein the training data comprises a structured data matrix, wherein columns of the data matrix represent the sensor data that are grouped in accordance with the data template and wherein rows of the data matrix represent timestamps of obtaining the sensor data; providing a pre-trained machine learning model using the determined process instance; and training a new machine learning model using the provided pre-trained model and the determined training data.

公开(公告)号：US20240337991A1

公开(公告)日：2024-10-10

申请号：US18744874

申请日：2024-06-17

Applicant: ABB Schweiz AG

Inventor： Georg Gutermuth ,  Matthias Biskoping ,  Felix Lenders ,  Bernhard Primas ,  Kai Koenig ,  Kalpesh Bhalodi

IPC: G05B13/04

CPC classification number: G05B13/041 ,  G05B13/048

Abstract: A method for establishing and/or improving a simulation model of an electrolyzer plant includes predicting one or more prediction values of at least one quantity; obtaining one or more measurement values of the same at least one quantity that relate to the same given operating state of the electrolyzer plant; determining at least one deviation of the one or more prediction values from the respective measurement values; determining from the deviation and the simulation model a contribution and/or an adjustment to the simulation model; and applying the contribution and/or the adjustment to the simulation model.