公开(公告)号：US20240106715A1

公开(公告)日：2024-03-28

申请号：US18474668

申请日：2023-09-26

Applicant: ABB Schweiz AG

Inventor： Andreas Burger ,  Heiko Koziolek ,  Pablo Rodriguez ,  Rhaban Hark

IPC: H04L41/12 ,  H04L41/0823

CPC classification number: H04L41/12 ,  H04L41/0823

Abstract: A method for automatic generation of a specification for an IT topology of a control system, the method comprising: creating a system structure from a machine-readable data defining production process requirements and generating specification data of the IT topology based on the extracted system structure; optimizing the generated specification data of the IT topology by utilization of pre-defined rules and generating abstract aggregated IT topology data based on the optimized specification data; and instantiating and mapping the abstract aggregated IT topology data to specific technology instance data.

公开(公告)号：US20240036931A1

公开(公告)日：2024-02-01

申请号：US18486536

申请日：2023-10-13

Applicant: ABB Schweiz AG

Inventor： Pablo Rodriguez ,  Heiko Koziolek ,  Andreas Burger ,  Julius Rueckert

IPC: G06F9/50

CPC classification number: G06F9/5044 ,  G06F9/5072 ,  G06F2209/503 ,  G06F2209/501 ,  G06F2209/5014

Abstract: A method for managing the transfer of a live containerized stateful process automation application from a source node to a target node of a process control system includes obtaining data relating to execution of the application at the source node and deriving from the data an application execution profile; obtaining an evaluation of available computing resources at the target node; determining feasibility of the transfer by comparing the available computing resources to the application execution profile; and in response to the transfer being determined to be feasible, initiating the transfer of the application from the source node to the target node.

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：US20230034769A1

公开(公告)日：2023-02-02

申请号：US17966012

申请日：2022-10-14

Applicant: ABB Schweiz AG

Inventor： Moncef Chioua ,  Marcel Dix ,  Benjamin Kloepper ,  Ioannis Lymperopoulos ,  Dennis Janka ,  Pablo Rodriguez

IPC: G05B13/02 ,  G05B23/02

Abstract: A method and computer program product including training a machine learning model by means of input data and score data, wherein the machine learning model is an artificial neural net, ANN; running the trained machine learning model by applying the first time-series to the trained machine learning model; and outputting, by the trained machine learning model, an output value, comprising at least a second criticality value of the at least one predicted observable process-value indicative of the abnormal behaviour of the industrial process in a predefined temporal distance.

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：US20240356801A1

公开(公告)日：2024-10-24

申请号：US18635155

申请日：2024-04-15

Applicant: ABB Schweiz AG

Inventor： Pablo Rodriguez ,  Dirk Schulz

IPC: H04L41/0806 ,  H04L41/12 ,  H04L47/2475 ,  H04L47/28 ,  H04L67/12

CPC classification number: H04L41/0806 ,  H04L41/12 ,  H04L47/2475 ,  H04L47/28 ,  H04L67/12

Abstract: A method for creating a configuration of a communication network, which includes networking and automation devices with embedded networking functions, the automation devices comprising communication endpoints providing and/or consuming application data of attached automation application functions running on the automation devices. The method includes communicating information about application functions and intents, receiving and resolving, by determining physical or virtual devices according to the network topology, to obtain identities and addresses of the communication endpoints; receiving timing information and further QoS requirements, and binding, taking into account the timing information and the further QoS requirements; creating qualified connectivity requests for the communication between the identifiable and addressable communication endpoints, and obtaining configuration information according to which the process network can be configured.

公开(公告)号：US20230080873A1

公开(公告)日：2023-03-16

申请号：US17993443

申请日：2022-11-23

Applicant: ABB Schweiz AG

Inventor： Dennis Janka ,  Benjamin Kloepper ,  Moncef Chioua ,  Pablo Rodriguez ,  Ioannis Lymperopoulos ,  Marcel Dix

IPC: G06F30/27

Abstract: A model generation system includes input and output units. The input unit receives a plurality of input value trajectories comprising operational input value trajectories and simulation input value trajectories relating to an industrial process. The processing unit implements a simulator of the industrial process and generates behavioral data for at least some of the plurality of input value trajectories. The processing unit further implements a machine learning algorithm that models the industrial process, and trains the machine learning algorithm.

公开(公告)号：US20220036207A1

公开(公告)日：2022-02-03

申请号：US17505665

申请日：2021-10-20

Applicant: ABB Schweiz AG

Inventor： Pablo Rodriguez ,  Jens Doppelhamer ,  Katharina Stark ,  Prerna Juhlin

IPC: G06N5/02

Abstract: A computer-implemented method of training an artificial intelligence module for selecting at least one component of an industrial drive system and an apparatus that includes a correspondingly trained AI module are described. The method includes providing an initial training data set that includes a set of rules, where each rule is indicative of a selection decision for selecting at least one component of the industrial drive system based on at least one usage requirement for the industrial drive system. Further, a modified training data set is generated based on supplementing the initial training data set with at least one further selection decision for selecting the at least one component of the drive system based on at least one of simulation data, empiric data, and operational data. Further, the AI module is trained based on the modified training data set.

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：US12284083B2

公开(公告)日：2025-04-22

申请号：US18474668

申请日：2023-09-26

Applicant: ABB Schweiz AG

Inventor： Andreas Burger ,  Heiko Koziolek ,  Pablo Rodriguez ,  Rhaban Hark

IPC: H04L41/12 ,  H04L41/0823

Abstract: A method for automatic generation of a specification for an IT topology of a control system, the method comprising: creating a system structure from a machine-readable data defining production process requirements and generating specification data of the IT topology based on the extracted system structure; optimizing the generated specification data of the IT topology by utilization of pre-defined rules and generating abstract aggregated IT topology data based on the optimized specification data; and instantiating and mapping the abstract aggregated IT topology data to specific technology instance data.