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Optimal Monitoring of Multivariate Data for Fault Patterns

Summary: [This abstract is based on the authors' abstract.]The process-oriented basis representation (POBREP) can be used to express multivariate quality vectors as linear combinations of fault patterns, plus a residual. To use these methods for monitoring changes in the mean of the quality vector, it is necessary to identify whether the effects occur only as special causes or also as common causes of variation. Usually, the coefficients must be computed by weighted least squares, but it is shown that in some circumstance, the ordinary least squares estimates are equivalent. In such cases, charting the proposed U(2) statistic is equivalent to charting a T(2) statistic computed from the process-oriented coefficients. It is shown that the POBREP approach yields substantially better average run-length performance compared to the usual T(2) chart applied to the original quality vectors.

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  • Topics: Statistical Process Control (SPC), Quality Control
  • Keywords: Control charts, Multivariate quality control, Monitoring, Statistical process control (SPC)
  • Author: Runger, George C.; Barton, Russell R.; Del Castillo, Enrique; Woodall, William H.
  • Journal: Journal of Quality Technology