자기상관 공정에 대한 누적합관리도에서 설계모수 값의 결정 = A note on CUSUM design for autocorrelated processes

다국어 초록 (Multilingual Abstract)

It is common to use CUSUM charts for detecting small level shifts in processes control, in which reference value (k) and decision interval(h) are the design parameters to be determined. To control process with auto-correlation, CUSUM charts could be applied to residuals obtained from fitting ARIMA models. However, constant level shifts in processes lead to varying mean shifts in residual processes and thus standard CUSUM charts may need to be modified. In this paper, we study the performance of CUSUM charts with various design parameters applied to autocorrelated processes, especially focussing on ARMA(1,1) models, and propose how they can be determined to get better performance in terms of the average run length.

참고문헌 (Reference)

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2 Douglas C. Montgomery, "Some Statistical Process Control Methods for Autocorrelated Data" 23 (23): 179-197, 1991

3 이재준, "Problems of Special Causes in Feedback Adjustment" 한국품질경영학회 32 (32): 201-211, 2004

4 Douglas M. Hawkins, "Cumulative Sum Charts and Changing for Quality Improvement" Sringer 1997

5 S.Jack Hu, "Change Patterns of Time Series Based Control Charts" 28 (28): 302-312, 1996

6 Runger G. C., "Batch Mean Control Charts for Autocorrelated Data" 28 (28): 483-487, 1996

7 George C Runger, "Average Run Length for CUSUM Control Charts Applied to Residuals" 24 (24): 273-282, 1995