원문정보
Sensitivity Analysis of Control Charts using EWMA Forecasting Models
초록
영어
It is revealed that, as the use of automated manufacturing process is increasing and the process inspection technology is improvement in industry for recently years, the data from mass production system will exhibit some degree of autocorrelation. Therefore, using the EWMA forecast models which has been proposed as a very good forecasting tool when autocorrelated construction contacted with time-series models is explained, I want to analysis sensitivity of quality control charts considering the variation of error or forecast residuals. In this paper, for the AR(1) process of EWMA forecast model, when the constant term ξ are zero and different from zero, the results of analyzed the sensitivity of Χ, CUSUM and EWMA control chart using EWMA forecast residuals are summarized as follows. First, the EWMA statistic is known as a good alternative to the Box-Jenkins forecasts for a variety of time-series models, the violation of the independence assumption can also lead to suboptimal monitoring schemes, particularly for the EWMA and the CUSUM control charts applied to EWMA forecast residuals, and particularly sensitive to the presence of autocorrelation For example, when θ₁ is underestimated, the EWMA and the CUSUM control charts applied to the EWMA forecast residuals provide ARLs which are much larger than anticipated. When θ₁is overestimated, the EWMA and the CUSUM control charts applied to the EWMA forecast residuals provide smaller ARLs than anticipated. Second, for EWMA forecasting model, whether ξ is zero or ξ is different from zero, the performance of control charts is equality. Therefor, the violation of the independence assumption can lead to suboptimal monitoring schemes, particularly for the EWMA and the CUSUM control charts applied to forecast errors. In this cases, whether one could adjust the control limits of the EWMA and the CUSUM control charts applied to forecast errors to obtain the desired in-control ARLs or when either underestimation in θ₁, or overestimation in θ₁, the Shewhart control chart is recommended since it is least sensitive to the violation of the independence assumption.
목차
II. 자기상관관계에 의한 예측기법
1. 자기상관관계의 기존연구
2. EWMA 통계량 예측모형
3. EWMA 예측잔차에서 추정오차의 영향
III. EWMA 통계량 예측모형의 민감도 분석
IV. 결론
참고문헌
Abstract