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AuthorAbbas, Tahir
AuthorAbbasi, Saddam Akber
AuthorRiaz, Muhammad
AuthorQian, Zhengming
Available date2023-05-28T10:11:27Z
Publication Date2019
Publication NameComputers and Industrial Engineering
ResourceScopus
URIhttp://dx.doi.org/10.1016/j.cie.2018.12.001
URIhttp://hdl.handle.net/10576/43499
AbstractLinear profiles monitoring have been successfully implemented in many industrial applications. The design structures of control charts for profiles monitoring are mostly based on two major classifications namely Classical and Bayesian. This study investigates the novel Bayesian exponentially weighted moving average and multivariate exponentially weighted moving average control charts for the monitoring of linear profiles, when explanatory variable(s) are random. The informative priors of normal and inverse gamma; and Bramwell, Holdsworth, Pinton (BHP) and Levy distributions are considered as conjugate and non-conjugate priors respectively. The proposed Bayesian schemes are evaluated using different run length characteristics. The schemes are also validated with simulation study and real-world data sets. The outcomes demonstrate that the Bayesian methods perform effectively better than the competing methods. The specified values of hyper-parameters are selected carefully after elicitation and sensitivity analysis of hyper-parameters. It has been observed that careful consideration is required while selecting the priors and possible values of hyper-parameters. The selection of appropriate priors and corresponding hyper-parameters comes up with efficient control structures which provide tangible benefits. 2018 Elsevier Ltd
SponsorThe authors would like to acknowledge the Editor and Referees for their constructive comments that lead to significant improvements in the manuscript. The authors would like to acknowledge their parent Universities for providing excellent research facilities. Moreover, Dr. Muhammad Riaz would like to acknowledge Deanship of Scientific Research for supporting the study under Project Number IN171016.
Languageen
PublisherElsevier
SubjectHyper-parameters
Posterior distributions
Prior distributions
Run length properties
Statistical process control
TitlePhase II monitoring of linear profiles with random explanatory variable under Bayesian framework
TypeArticle
Pagination1115-1129
Volume Number127
dc.accessType Abstract Only


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