A new variable sampling control scheme at fixed times for monitoring the process dispersion

Authors

  • Lihui Shi,

    1. Industrial Engineering, Box 352650, University of Washington, Seattle, WA 98195-2650, U.S.A.
    2. LPMC and Department of Statistics, School of Mathematical Sciences, Nankai University, Tianjin 300071, People's Republic of China
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  • Changliang Zou,

    1. LPMC and Department of Statistics, School of Mathematical Sciences, Nankai University, Tianjin 300071, People's Republic of China
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  • Zhaojun Wang,

    Corresponding author
    1. LPMC and Department of Statistics, School of Mathematical Sciences, Nankai University, Tianjin 300071, People's Republic of China
    • LPMC and Department of Statistics, School of Mathematical Sciences, Nankai University, Tianjin 300071, People's Republic of China
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  • Kailash C. Kapur

    1. Industrial Engineering, Box 352650, University of Washington, Seattle, WA 98195-2650, U.S.A.
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Abstract

The variable sampling rate (VSR) schemes for detecting the shift in process mean have been extensively analyzed; however, adding the VSR feature to the control charts for monitoring process dispersion has not been thoroughly investigated. In this research, a novel VSR control scheme, sequential exponentially weighted moving average inverse normal transformation (EWMA INT) at fixed times chart (called (SEIFT) chart), which integrates the sequential EWMA scheme at fix times with the INT statistic, is proposed to detect both the increase and decrease in process dispersion. Moreover, the sample size at each sampling time is also allowed to vary. The Markov chain method is used to evaluate the performance of this new control chart. Numerical analysis reveals that this SEIFT chart gives significant improvement on detection ability than the fixed sampling rate schemes. Compared with other control schemes, the good properties of the INT statistic makes this SEIFT chart easy to design and convenient to implement. Copyright © 2009 John Wiley & Sons, Ltd.

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