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Quality Quandaries : Practical Time Series Modeling

Summary: Automated sensors permit a high rate of data sampling from industrial processes, but when sampled quickly, the process data will often be positively autocorrelated. If autocorrelation is ignored, traditional quality control procedures can be misleading. Time series analysis provides a means of studying how to alleviate potentially harmful effects on such methods and helps in the development of alternative methods. While time series analysis can be complicated, quality engineers can gain familiarity with the theory from working through examples provided by standard software packages. A detailed analysis of a time series example from the literature demonstrates that there are no precise methods and no true final answer when engaged in time series modeling.

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  • Topics: Engineering
  • Keywords: Quality control methodology, Time series, ARIMA time series models, Autocorrelation
  • Author: Søren Bisgaard; Murat Kulahci
  • Journal: Quality Engineering