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Monitoring and Diagnosing Multistage Processes: A Review of Cause Selecting Control Charts

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A review of the literature on cause selecting charts (CSCs) in multistage processes is given, with a concentration on developments which have occurred since 1993. Model based control charts and multiple cause selecting charts (MCSCs) are reviewed. Several articles based on normally and non-normally distributed outgoing quality characteristics are analyzed and important issues such as economic design, autocorrelated processes and adaptive design parameters of cause selecting charts are discussed. The results reveal that cause selecting charts outperform traditional Shewhart charts for individuals when the process steps are dependent, in view of the relationship between input and output quality characteristics. A new method for modeling and simulating a multistage process is proposed which can prove to be more reasonable in real practice. Finally, various directions for future research are given.

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