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An Adaptive Synthetic Control Chart for Detecting Shifts in the Process Mean

  • 임태진 (숭실대학교 산업ㆍ정보시스템공학과)
  • 발행 : 2004.12.01

초록

The synthetic control chart (SCC) proposed by Wu and Spedding (2000) is to detect shifts in the process mean. The performance was re-evaluated by Davis and Woodall (2002), and the steady-state average run length (ARL) performance was shown to be inferior to cumulative sum (CUSUM) or exponentially weighted moving average (EWMA) chart This paper proposes a simple adaptive scheme to improve the performance of the synthetic control chart. That is, once a non-conforming (NC) sample occurs, we investigate the next L-consecutive samples with larger sample sizes and shorter sampling intervals. We employ a Markov chain model to derive the ARL and the average time to s19na1 (ATS). We also propose a statistical design procedure for determining decision variables. Comprehensive comparative study shows that the proposed control chart is uniformly superior to the original SCC or double sampling (DS) Χ chart and comparable to the EWMA chart in ATS performance.

키워드

참고문헌

  1. Davis, R. B. and Woodall W. H. (2002). 'Evaluating and Improving the Synthetic Control Chart'. Journal of Quality Technology 34, pp. 200-208 https://doi.org/10.1080/00224065.2002.11980146
  2. Daudin, J. J. (1992). 'Double Sampling Charts'. Journal of Quality Technology 24, pp. 78-87
  3. Lucas, J. M. and Saccucci, M. S. (1990). 'Exponentially Weighted Moving Average Control Schemes: Properties and Enhancements'. Technometrics 32, pp. 1-12 https://doi.org/10.2307/1269835
  4. Wu, Z. and Spedding, T. A. (2000). 'A Synthetic Control Chart for Detecting Small Shifts in the Process Mean'. Journal of Quality Technology 32, pp. 32-38 https://doi.org/10.1080/00224065.2000.11979969