Determining Optimal Number of Samples for Constructing Multivariate Control Charts |
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| Authors: | Sheau-Chiann Chen |
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| Institution: | 1. Department of Statistics , National Cheng Kung University , Tainan, Taiwan;2. Department of Applied Mathematics , National Chiayi University , Chiayi, Taiwan |
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| Abstract: | Normally, an average run length (ARL) is used as a measure for evaluating the detecting performance of a multivariate control chart. This has a direct impact on the false alarm cost in Phase II. In this article, we first conduct a simulation study to calculate both in-control and out-of-control ARLs under various combinations of process shifts and number of samples. Then, a trade-off analysis between sampling inspection and false alarm costs is performed. Both the simulation results and trade-off analysis suggest that the optimal number of samples for constructing a multivariate control chart in Phase I can be determined. |
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| Keywords: | Average run length Multivariate control chart Standard deviation run length |
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