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：US20210260754A1

公开(公告)日：2021-08-26

申请号：US17317920

申请日：2021-05-12

Applicant: ABB Schweiz AG

Inventor： Pablo Rodriguez ,  Benjamin Kloepper ,  Arzam Muzaffar Kotriwala ,  Marcel Dix ,  Debora Clever ,  Fan Dai

IPC: B25J9/16 ,  G05B13/02 ,  G05B13/04

Abstract: A method for applying machine learning to an application includes: a) generating a set of candidate parameters by a learner; b) executing a program in at least one simulated application based on the set of candidate parameters and providing interim results of tested sets of candidate parameters based on a measured performance information of the execution of the program; c) collecting a predetermined number of interim results and providing an end result based on a combination of the candidate parameters and the measured performance information by a trainer; and d) generating a new set of candidate parameters by the learner based on the end result for execution by the unchanged program.

公开(公告)号：US20250013279A1

公开(公告)日：2025-01-09

申请号：US18762839

申请日：2024-07-03

Applicant: ABB Schweiz AG

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

IPC: G06F1/26 ,  G05B15/02

Abstract: A computer-implemented method for determining an energy load distribution in a system, comprising: receiving total energy load data of the system, wherein the total energy load data comprises individual energy load data of a plurality of assets; determining at least one energy load peak in the total energy load data; disaggregating the total energy load data into the individual energy load data of the plurality of assets; providing the disaggregated individual energy load data of the plurality of assets for further processing.

公开(公告)号：US20240426879A1

公开(公告)日：2024-12-26

申请号：US18746180

申请日：2024-06-18

Applicant: ABB Schweiz AG

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

IPC: G01R19/25 ,  H02J3/00 ,  H02J3/38

Abstract: A method for determining an energy ratio includes providing an energy network model configured to describe an energy flow between a plurality of assets in an energy network, the assets including energy sources and consumers; receiving load demand and power source data; controlling and tracking the first energy flow from the first energy source to the plurality of assets in the energy network and the second energy flow from the second energy source to the plurality of assets in the energy network based on the energy network model and the received load demand data and the received power source data; tracking one or more consuming times of the at least one energy consuming asset; and determining an energy ratio for the at least one energy consuming asset based on the tracked first energy flow and the second energy flow and the tracked consuming time of an energy consuming asset.

公开(公告)号：US12007745B2

公开(公告)日：2024-06-11

申请号：US17480165

申请日：2021-09-21

Applicant: ABB Schweiz AG

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

IPC: G05B23/02 ,  G05B19/4065 ,  G06F18/23213 ,  G06N3/045

CPC classification number: G05B19/4065 ,  G05B23/024 ,  G06F18/23213 ,  G06N3/045 ,  G05B2219/37252

Abstract: An apparatus includes an input unit, a processing unit, and an output unit. The input unit is configured to provide the processing unit with sensor data for an item of equipment. The processing unit is configured to implement at least one machine learning algorithm, which has been trained on the basis of a plurality of calibration sensor data for the item of equipment. Training of the at least one machine learning algorithm includes processing the plurality of calibration sensor data to determine at least two clusters representative of different equipment states. The processing unit is configured to implement the at least one machine learning algorithm to process the sensor data to assign the sensor data to a cluster of the at least two clusters to determine an equipment state for the item of equipment. The output unit is configured to output the equipment state for the item of equipment.

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：US20250117537A1

公开(公告)日：2025-04-10

申请号：US18929853

申请日：2024-10-29

Applicant: ABB Schweiz AG

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

IPC: G06F30/18 ,  G06F30/27 ,  G06F113/14

Abstract: A method for interactive explanations in industrial artificial intelligence systems includes providing a machine learning model and a set of test data, a set of training data and a set of historical data simulating a piping and process equipment; predicting a result for the piping and process equipment based on the machine learning model using the set of test data and the set of training data, wherein the set of historical data is used by the machine learning model to predict at least one parameter of the piping and process equipment; and presenting the predicted at least one parameter on a piping and instrumentation diagram of the piping and process equipment.

公开(公告)号：US20250110493A1

公开(公告)日：2025-04-03

申请号：US18978207

申请日：2024-12-12

Applicant: ABB Schweiz AG

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

IPC: G05B23/02

Abstract: A method for recommending an operational command includes receiving an alarm from a sensor and/or an operator; obtaining the current state of the plant that includes a current process value and/or operational command; comparing the current state to a list of historic states, each comprising a plurality of historic process values and/or historic operational commands; when the current state matches a subset of at least one of the historic states, starting a simulation and running a plurality of simulations, each based on a variation of at least one of the historic operational commands; determining, for each simulation of the plurality of simulations, a quality value, based on at least one quality criterion; and recommending the variation of the operational command that resulted in the simulation with the highest quality value.

公开(公告)号：US20250053879A1

公开(公告)日：2025-02-13

申请号：US18928369

申请日：2024-10-28

Applicant: ABB Schweiz AG

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

IPC: G06N20/00

Abstract: A method for enabling user feedback and summarizing return of investment for machine learning systems includes providing a training data set and an initial machine learning model; providing a result of the initial machine learning model; receiving feedback on the result of the initial machine learning model from a user enriching the training dataset based on the feedback to an enriched data set; and retraining the initial machine learning model to a retrained machine learning model based on an enriched data set.