A new nonparametric EWMA Sign Control Chart

  • Authors:
  • Su-Fen Yang;Jheng-Sian Lin;Smiley W. Cheng

  • Affiliations:
  • Department of Statistics, National Chengchi University, Muzha, Taipei 116, Taiwan, ROC;Department of Statistics, National Chengchi University, Muzha, Taipei 116, Taiwan, ROC;Department of Statistics, University of Manitoba Winnipeg, Manitoba, Canada R3T 2N2

  • Venue:
  • Expert Systems with Applications: An International Journal
  • Year:
  • 2011

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Abstract

Many data in practice came from a population/process with a non-normal or often unknown distribution, hence the commonly-used Shewhart control chart, which requires normality of the monitoring statistics, is not suitable. In this paper, a new nonparametric EWMA Sign Control Chart is proposed for monitoring and detecting possible deviation from the process target. The sampling properties of the new monitoring statistics are examined and the average run lengths of the proposed chart are derived for evaluating its performance. An example is used to illustrate the proposed chart and compare with other existing charts, assuming normality. Furthermore, an arcsine transformed EWMA Sign Chart is examined and proposed. The average run lengths of the Arcsine EWMA Chart are more reasonable than those of the EWMA Sign Chart. The Arcsine EWMA Sign Chart is recommended if we were concerned with the proper values of the average run length.