| Summary: | 碩士 === 國立交通大學 === 工業工程與管理系 === 90 === The process capability indices are utilized to evaluate a supplier’s general process capability. A larger process index value usually leads to a more capable production process, that is, more products will meet the specifications. However, conventional process capability indices can not accurately evaluate the performance of a non-normal distribution process. This inability would lead to an engineer making misleading when comparing processes or selecting an alternative material supplier. CNp,, CNpk,, CNpm and CNpmk which adopt Clements’ method are more efficient than conventional PCIs with non-normal distribution process, among the available process capability indices, CNpmk is the newest and most efficient index.
Generally speaking, the probability distribution function of an estimated process capability index can develop the related hypotheses testing and confidence interval to accurately evaluate a certain process. However, the exact probability distribution of CNpmk is too complicated, only the approximate probability distribution of , which is the estimators of CNpmk, can be derived. Therefore, the main objective of this study is to utilize Bootstrap simulation method to construct confidence intervals for the difference between two CNpmk under a non-normal process distribution. The confidence interval of the difference between two CNpmk is utilized to compare two processes or select an alternative material supplier. A detailed procedure was written so that process engineers can construct the confidence interval of the difference between two CNpmk flexibly and efficiently. Finally, there were two real-world process data been employed to illustrate the effectiveness of the processed method.
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