Computer-implemented determination of a quality indicator of a production batch-run of a production process

    公开(公告)号:US12147222B2

    公开(公告)日:2024-11-19

    申请号:US17500982

    申请日:2021-10-14

    Applicant: ABB Schweiz AG

    Abstract: To determine a quality indicator of production batch-run of a production process, a computer compares time-series with multi-source data from a reference batch-run and time-series with multi-source data from the production batch-run. Before comparing, the computer converts multi-variate time-series to uni-variate time-series, by first multiplying data values of source-specific uni-variate time-series with source-specific factors from a conversion factor vector and second summing up the multiplied data values according to discrete time points. The source-specific factors of the conversion factor vector are obtained earlier by processing reference data, including the determination of characteristic portions of the time-series, converting, aligning by time-warping and evaluating displacement in time between characteristic portions before alignment and after alignment.

    COMPUTER-IMPLEMENTED DETERMINATION OF A QUALITY INDICATOR OF A PRODUCTION BATCH-RUN OF A PRODUCTION PROCESS

    公开(公告)号:US20220035351A1

    公开(公告)日:2022-02-03

    申请号:US17500982

    申请日:2021-10-14

    Applicant: ABB Schweiz AG

    Abstract: To determine a quality indicator of production batch-run of a production process, a computer compares time-series with multi-source data from a reference batch-run and time-series with multi-source data from the production batch-run. Before comparing, the computer converts multi-variate time-series to uni-variate time-series, by first multiplying data values of source-specific uni-variate time-series with source-specific factors from a conversion factor vector and second summing up the multiplied data values according to discrete time points. The source-specific factors of the conversion factor vector are obtained earlier by processing reference data, including the determination of characteristic portions of the time-series, converting, aligning by time-warping and evaluating displacement in time between characteristic portions before alignment and after alignment.

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