Computer-implemented method for obtaining parameters to be used by a control module of a computer, wherein the control module is adapted to control technical equipment by processing batch-run data from the technical equipment by aggregating data from a particular interaction-time batch-run of the technical equipment into a status indicator of the technical equipment and/or a quality indicator for the interaction-time batch-run, wherein the interaction-time batch-run is a current batch-run or a historic batch-run, the method comprising: receiving, from technical equipment that has performed a production process, a reference plurality of multi-variate reference time-series (510-e), wherein the multi-variate reference time-series (510-e) are based on time points (t k) of a batch-specific batch-run time interval ([t 1, t K]) and comprises data values from sources (120-1, 120-2, 120-5) that are related to the technical equipment, wherein each multi-variate reference time-series (510-e) comprises a first time-series (511-e) from a first source, with data for first measurement values, a second time-series (512-e) from a second source, with data for second measurement values, and a third time-series (515-e) from a third source, with data describing particular manufacturing operations during the batch-run time interval ([t 1, t K]); for each multi-variate reference time-series (510-e) of the plurality separately: splitting the batch-run time interval ([t 1, t K]) into phases (p), the phases (p) being consecutive time intervals ([t 1, t N]p), by determining transitions between the particular manufacturing operations, and dividing the first time-series (511-e) into particular phase-specific first partial series (511-1e, 511-2e) and the second time-series into particular phase-specific second partial series (512-1e, 512-2e); for each phase (p) separately, and for the phase-specific partial series in combination, processing the phase-specific partial series to differentiate the plurality-related phase-specific time-series into relevant partial time-series or non-relevant partial time-series according to relevance rules, characterised by wherein processing to differentiate is executed by evaluating any of the following relevance rules, using: magnitude of data values within a pre-defined threshold band, relation of data values to the standard deviation of the normal distribution, signal-to-noise ratio, Dynamic Time Warping distances, identification of time-series that are correlated, and the identification of outliers in disturbed time-series; and storing the relevance information as the parameters, wherein storing the relevance information is executed by providing a parameter matrix (Φ), whose rows relate to particular sources v, and whose columns relate to particular phases p, with binary elements that selectively allow or block the control module of the computer to process the batch-run data from the technical equipment wherein an element "0" of the parameter matrix (Φ) indicates data to be processed, and an element "1" of the parameter matrix (Φ) indicates data to disregard. receiving, from technical equipment that has performed a production process, a reference plurality of multi-variate reference time-series (510-e), wherein the multi-variate reference time-series (510-e) are based on time points (t k) of a batch-specific batch-run time interval ([t 1, t K]) and comprises data values from sources (120-1, 120-2, 120-5) that are related to the technical equipment, wherein each multi-variate reference time-series (510-e) comprises a first time-series (511-e) from a first source, with data for first measurement values, a second time-series (512-e) from a second source, with data for second measurement values, and a third time-series (515-e) from a third source, with data describing particular manufacturing operations during the batch-run time interval ([t 1, t K]); for each multi-variate reference time-series (510-e) of the plurality separately: splitting the batch-run time interval ([t 1, t K]) into phases (p), the phases (p) being consecutive time intervals ([t 1, t N]p), by determining transitions between the particular manufacturing operations, and dividing the first time-series (511-e) into particular phase-specific first partial series (511-1e, 511-2e) and the second time-series into particular phase-specific second partial series (512-1e, 512-2e); for each phase (p) separately, and for the phase-specific partial series in combination, processing the phase-specific partial series to differentiate the plurality-related phase-specific time-series into relevant partial time-series or non-relevant partial time-series according to relevance rules, characterised by wherein processing to differentiate is executed by evaluating any of the following relevance rules, using: magnitude of data values within a pre-defined threshold band, relation of data values to the standard deviation of the normal distribution, signal-to-noise ratio, Dynamic Time Warping distances, identification of time-series that are correlated, and the identification of outliers in disturbed time-series; and storing the relevance information as the parameters, wherein storing the relevance information is executed by providing a parameter matrix (Φ), whose rows relate to particular sources v, and whose columns relate to particular phases p, with binary elements that selectively allow or block the control module of the computer to process the batch-run data from the technical equipment wherein an element "0" of the parameter matrix (Φ) indicates data to be processed, and an element "1" of the parameter matrix (Φ) indicates data to disregard.