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Change Patterns of Time Series-Based Control Charts

Summary: [This abstract is based on the authors' abstract.]

Autocorrelation in process measurements results in false alarms when traditional control charts are applied in process monitoring. Frequently, time series models are used to remove the autocorrelation, but the change patterns may be severely altered, making interpretation of results erroneous. Charts are developed for the comparison of change patterns for two types of additive process faults before and after applying time series modeling. These charts clarify the characteristics of autocorrelated processes.

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  • Topics: Statistical Process Control (SPC)
  • Keywords: Control charts,Statistical process control (SPC),Time series,Measurement error
  • Author: Hu, Jack S.; Roan, Chinmo
  • Journal: Journal of Quality Technology