公开(公告)号：US20230274189A1

公开(公告)日：2023-08-31

申请号：US18171732

申请日：2023-02-21

Applicant: ABB Schweiz AG

Inventor： Arzam Muzaffar Kotriwala ,  Benjamin Kloepper ,  Ido Amihai ,  Taisuke Minagawa ,  Dominik Olschewski ,  Kai Merz

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: A system and method for outlier detection based on process fingerprints from robot cycle data includes a data collection component, which is configured to collect cyclic data, wherein the cyclic data comprises multiple vectors each of which comprises data from one individual cycle of the robot cycle data; a data storage component, wherein which is configured to store the collected cyclic data; and a data processing component, which is configured to perform cloud processing of the stored cyclic data triggered by a cycle-start signal, wherein the data processing component is configured to parse the stored cyclic data and to process the stored cyclic data based on a configuration file defining metadata of the stored cyclic data, wherein the data processing component is configured extract process fingerprints from the stored cyclic data using the metadata.

公开(公告)号：US20230237284A1

公开(公告)日：2023-07-27

申请号：US18193809

申请日：2023-03-31

Applicant: ABB Schweiz AG

Inventor： Benedikt Schmidt ,  Marco Gaertler ,  Sylvia Maczey ,  Pablo Rodriguez ,  Benjamin Kloepper ,  Arzam Muzaffar Kotriwala ,  Nuo Li

IPC: G06F40/58 ,  G06F40/30 ,  H04L67/50

CPC classification number: G06F40/58 ,  G06F40/30 ,  H04L67/535

Abstract: A method for controlling a virtual assistant for an industrial plant includes receiving by an input interface an information request, wherein the information request comprises at least one request for receiving information about at least part of the industrial plant; determining by a control unit a model specification using the received information request; determining by a model manager a machine learning model using the model specification; and providing by the control unit a response to the information request using the determined machine learning model.

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：US20210264317A1

公开(公告)日：2021-08-26

申请号：US17317926

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: G06N20/00 ,  G06F30/20 ,  B25J9/16

Abstract: A method for applying machine learning to an application includes: a) generating a candidate policy by a learner; b) executing a program in at least one simulated application based on a set of candidate parameters provided based on the candidate policy and a state of the at least one simulated application, execution of the program 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/or the state with the measured performances information by a trainer; and d) generating a new candidate policy by the learner based on the end result.

公开(公告)号：US11069356B2

公开(公告)日：2021-07-20

申请号：US16988732

申请日：2020-08-10

Applicant: ABB Schweiz AG

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

IPC: G10L15/22 ,  G10L15/30 ,  G05B19/042

Abstract: A computer system for controlling a dialogue between a user and the computer system, the computer system being communicatively coupled with an industrial control system controlling an industrial system, the computer system including: an interface for receiving intent inputs representing a respective desired interaction with the computer system; an intent determination module for determining the desired interactions of received intent inputs; a data storage for storing one or more directed graphs, each graph specifying an industrial control domain specific dialogue, a particular graph defining a dialogue state machine with a plurality of nodes representing states of the dialogue, and with edges representing transitions between the states, each state transition from a first state to a second state depending on at least one precondition, the desired interaction of a received intent input corresponding to a target node to be reached from a current node of the particular graph.

公开(公告)号：US20210166684A1

公开(公告)日：2021-06-03

申请号：US16988732

申请日：2020-08-10

Applicant: ABB Schweiz AG

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

IPC: G10L15/22 ,  G10L15/30 ,  G05B19/042

Abstract: A computer system for controlling a dialogue between a user and the computer system, the computer system being communicatively coupled with an industrial control system controlling an industrial system, the computer system including: an interface for receiving intent inputs representing a respective desired interaction with the computer system; an intent determination module for determining the desired interactions of received intent inputs; a data storage for storing one or more directed graphs, each graph specifying an industrial control domain specific dialogue, a particular graph defining a dialogue state machine with a plurality of nodes representing states of the dialogue, and with edges representing transitions between the states, each state transition from a first state to a second state depending on at least one precondition, the desired interaction of a received intent input corresponding to a target node to be reached from a current node of the particular graph.

公开(公告)号：US20200012270A1

公开(公告)日：2020-01-09

申请号：US16576832

申请日：2019-09-20

Applicant: ABB Schweiz AG

Inventor： Martin Hollender ,  Benjamin Kloepper ,  Michael Lundh ,  Moncef Chioua

IPC: G05B23/02 ,  G05B13/04

Abstract: An anomaly detection module is configured to apply a plurality of machine learning models to received technical status data to detect one or more indicators of an abnormal technical status prevailing in the industrial process system. The plurality of machine learning models are trained on historic raw or pre-processed sensor data and the anomaly detection module configured to generate the anomaly alert based on the one or more indicators. The received technical status data is assigned to signal groups and the generated anomaly alert is a vector with each vector element representing a group anomaly indicator for the respective signal group. Each vector element is determined by applying a respective group specific machine learning model.