Time-series analysis in analytical process control |
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Authors: | Klaus Doerffel Rainer Niedtner Uwe Raschke Sigrid Blase |
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Institution: | Technical University “Carl Schorlemmer”; Leuna-Merseburg DDR 4200 Merseburg G.D.R.;BUNA AG, DDR 4220 Schkopau G.D.R. |
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Abstract: | Analysis of time series tries to extract tendencies from measured values dependent on time. For this purpose the cusum technique has proved to be a very sensitive tool for the evaluation of both current and completed time series. Even very weak tendencies can be detected at a high level of noise. Time-series analysis further tries to predict values to come from hitherto performed measurements. As a very flexible model exponential smoothing could be successfully used. Even for processes with a high extent of non-stationarity this model allowed a good prediction owing to the dynamics of the process. Three types of time-series analysis, i.e., evaluation of current measurements, retrospective evaluation and prediction of data (also known as “in vivo”, “post mortem” and “in futurum” time-series analysis) are demonstrated for problems stemming from analytical process control. |
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Keywords: | Process analysis Time-series analysis |
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