PARAMETRIC ESTIMATION OF THE PROCESS CAPABILITY INDEX S''pk AND ITS APPLICATION TO ELECTRONIC INDUSTRIES.

The proposed index is the process capability index used in the electronics industries to measure the capability of the process. This article focuses on process capability index, specifically applicable to normal random variables. The article has three main objectives: Firstly, we explore various classical estimation methods for the proposed index from frequentist approaches for normal distributions and compare their performance based on mean squared errors. Second, we calculate the classical confidence interval for the proposed index, which includes the asymptotic confidence interval. Third, we examine both Bayes point and interval estimation under symmetric and asymmetric loss functions for the proposed index. A Monte Carlo and Markov Chain Monte Carlo simulation study is conducted to compare the performance of the classical and the Bayes estimates of the proposed index for some set of parameters. Finally, to demonstrate the applicability of this index, two real data sets from the electronics industry are re-analyzed. [ABSTRACT FROM AUTHOR]

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