On the Plug-in Estimator and its Asymptotic Distribution Results for Vector-Valued Process Capability Index Cpmk

Title & Authors
On the Plug-in Estimator and its Asymptotic Distribution Results for Vector-Valued Process Capability Index Cpmk
Cho, Joong-Jae; Park, Byoung-Sun;

Abstract
A higher quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. The third generation index $\small{C_{pmk}}$ is more powerful than two useful indices $\small{C_p}$ and $\small{C_{pk}}$ that have been widely used in six sigma industries to assess process performance. In actual manufacturing industries, process capability analysis often entails characterizing or assessing processes or products based on more than one engineering specification or quality characteristic. Since these characteristics are related, it is a risky undertaking to represent the variation of even a univariate characteristic by a single index. Therefore, the desirability of using vector-valued process capability index(PCI) arises quite naturally. In this paper, we consider more powerful vector-valued process capability index $\small{C_{pmk}}$ = ($\small{C_{pmkx}}$, $\small{C_{pmky}}$)$\small{^t}$ that consider the univariate process capability index $\small{C_{pmk}}$. First, we examine the process capability index $\small{C_{pmk}}$ and plug-in estimator $\small{\hat{C}_{pmk}}$. In addition, we derive its asymptotic distribution and variance-covariance matrix $\small{V_{pmk}}$ for the vector valued process capability index $\small{C_{pmk}}$. Under the assumption of bivariate normal distribution, we study asymptotic confidence regions of our vector-valued process capability index $\small{C_{pmk}}$ = ($\small{C_{pmkx}}$, $\small{C_{pmky}}$)$\small{^t}$.
Keywords
Vector-valued process capability index;plug-in estimator;limiting distribution;variance covariance matrix;asymptotic confidence region;
Language
Korean
Cited by
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