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Author

Hossein Eghbali

Bio: Hossein Eghbali is an academic researcher. The author has contributed to research in topics: Control chart. The author has co-authored 1 publications.
Topics: Control chart

Papers
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Journal ArticleDOI
TL;DR: In this article, the authors evaluated the impact of measurement errors on the performance of various control charts and found that, as far as we know, the multiple sampling control charts in the lite setting were not affected.
Abstract: In recent years, the impact of measurement errors on the performance of various control charts have been well evaluated. However, as far as we know, the multiple sampling control charts in the lite...

3 citations


Cited by
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Journal ArticleDOI
TL;DR: In this article , the adverse effect of measurement errors on detecting performance of triple sampling (TS)- control chart based on an additive covariate model is investigated. And three multiple measurement based triple sampling schemes are developed to reduce the undesired impact of imprecise measurements on performance of TS- chart.
Abstract: ABSTRACT The presence of measurement errors can seriously alter the statistical performance of Phase II control charts. Up today, no research on designing the triple sampling control charts taking into account the gauge measurement errors is reported in the existing literature. In this paper, we study the adverse effect of measurement errors on detecting performance of triple sampling (TS)- control chart based on an additive covariate model. Three multiple measurement based triple sampling (MMBTS) schemes are developed to reduce the undesired impact of gauge inability on detecting performance of TS- chart. Through simulation studies in terms of average run length (ARL) and standard deviation of run length (SDRL), it is indicated that the run length characteristics of the TS- is significantly affected by the measurement errors. The results also confirm that all proposed remedial approaches can effectively reduce the undesired impact of imprecise measurements on performance of TS- chart. A sensitivity analysis is also carried out to evaluate how the covariate model parameters affect the detection performance of the TS- chart. Finally, using a real industrial data obtained from the spring production system, we demonstrate the performance of TS- chart when the measurement errors exist.

4 citations

Journal ArticleDOI
TL;DR: In this paper , a generalized multiple dependent state sampling (GMDS) chart based on ridge penalized likelihood ratio (RPLR ) statistic is developed for Phase II monitoring of multivariate process variability under high-dimensional setting.