Group Selection for One-Sided Processes with Multiple Characteristics

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The decision-maker usually faces the problem of selecting the best manufacturing material supplier – the one with the largest capability index – from several available suppliers in the initial stage of production setting. In this thesis, we consider the group selection problem for one-sided processes with multiple independent characteristics. More specifically, the aim of this thesis is to select all the possibly best suppliers into a group among k (k > 2) suppliers based on CpuT. An effective selection procedure is developed for practical applications. We apply the Bonferroni method to deal with multiple comparisons problem. For practitioners’ convenience, critical values for testing procedure and required sample sizes for a designated selection power are also investigated and tabulated. In addition, we compare the power between two multiple comparisons techniques, Bonferroni method and multiple comparisons with the best (MCB) method. The application examples for one-sided processes with multiple characteristics are presented to illustrate the practicality of this approach.