Controlling technical equipment through quality indicators using parameterized batch-run monitoring

    公开(公告)号:US11755605B2

    公开(公告)日:2023-09-12

    申请号:US17500972

    申请日:2021-10-14

    Applicant: ABB SCHWEIZ AG

    CPC classification number: G06F16/2477 G05B19/4183 G06F16/2379 G06F16/24556

    Abstract: A control module is adapted to control technical equipment by processing batch-run data from the technical equipment. The control module operates according to parameters that are obtained by a parameter module. The module receives a reference plurality of multi-variate reference time series with data values from sources that are related to the equipment. There are time series with measurement values and time series with data that describes particular manufacturing operations during a batch-run time interval. The module splits the time interval into phases by determining transitions between the particular manufacturing operations, and divides the time series into particular phase-specific partial series. For each phase separately, and for the phase-specific partial series in combination, the module differentiates phase-specific time series into relevant partial time series or non-relevant partial time series and set the parameters accordingly.

    Method for Generating a Process Model

    公开(公告)号:US20230050321A1

    公开(公告)日:2023-02-16

    申请号:US17977355

    申请日:2022-10-31

    Applicant: ABB Schweiz AG

    Abstract: A method for generating a process model modeling a manual mode procedure instance of a plant process includes providing log events of operational actions; selecting related sequences of manual mode operational actions from the log events; filtering the related sequences according to an individual plant section; identifying a sequential order from the filtered related sequences; determining statistical properties of values of related process variables and/or statistical properties of values of related set point changes to each sequential ordered manual mode operational action from the filtered related sequences; generating the process model of the manual mode procedure instance by arranging related manual mode operational actions with the sequential order of each operational action assigned with the statistical properties of the values of related process variables and/or assigned with the statistical properties of the values of the related set point changes.

    Method and System for Industrial Change Point Detection

    公开(公告)号:US20240160160A1

    公开(公告)日:2024-05-16

    申请号:US18455340

    申请日:2023-08-24

    Applicant: ABB Schweiz AG

    CPC classification number: G05B13/027

    Abstract: A method for detecting change points, CPs, in a signal of a process automation system, includes, in an offline learning phase, unsupervised, candidate CPs on at least one offline signal using unsupervised detection method are detected, CPs are selected from the candidate CPs; the selected CPs are provided to a supervised process; in the supervised process, an offline machine-learning (ML) system is trained to refine CPs from the selected CPs using a supervised machine learning method; a training data set for an online ML system is created using the offline ML system by projecting the refined CPs on the signal; the online ML system is trained in a supervised manner, using the created training data set; and after the offline learning phase, CPs are detected using the trained online ML system.

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