Adaptive control charts for skew-normal distribution

doi:10.1002/qre.2274

機構典藏 > College of Business and Management > Graduate Institute & Department of Statistics > Journal Article > Item 987654321/113678

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/113678

Title:	Adaptive control charts for skew-normal distribution
Authors:	Tsai, Tzong‐ru
Keywords:	adaptive control charts;average run length;cumulative sum charts;exponentially weighted movingaverage charts;Markov chain approach
Date:	2018-03-08
Issue Date:	2018-06-09 12:10:31 (UTC+8)
Abstract:	The standard Shewhart‐typeX chart, named FSS‐X chart, has been widely usedto detect the mean shift of process by implementing fixed sample and samplingfrequency schemes. The FSS‐X chart could be sensitive to the normality assump-tion and is inefficient to catch small or moderate shifts in the process mean. Tomonitor nonnormally distributed variables, Li et al [Commun Stat‐Theory Meth.2014; 43(23):4908‐4924] extended the study of Tsai [Int J Reliab Qual Saf Eng.2007; 14(1):49‐63] to provide a new skew‐normal FSS‐X (SN FSS‐X) chart withexact control limits for the SN distribution. To enhance the sensitivity of theSN FSS‐X chart on detecting small or moderate mean shifts in the process, adap-tiveX charts with variable sampling interval (VSI), variable sample size (VSS),and variable sample size and sampling interval (VSSI) are introduced for theSN distribution in this study. The proposed adaptive control charts include thenormality adaptive charts as special cases. Simulation results show that all theproposed SN VSI‐X, SN VSS‐X, and SN VSSI‐X charts outperform the SN FSS‐X chart on detecting small or moderate shifts in the process mean. The impactof model misspecification on using the proposed adaptive charts and the samplesize impact for using the FSS‐X chart to monitor the mean of SN data are alsodiscussed. An example about single hue value in polarizer manufacturingprocess is used to illustrate the applications of the proposed adaptive charts.
Relation:	Quality and Reliability Engineering International 34(4),　p.589-608
DOI:	10.1002/qre.2274
Appears in Collections:	[Graduate Institute & Department of Statistics] Journal Article

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