Abstract
In this article, we propose a new process capability index called C pmc ′ which is based on asymmetric loss function (linear exponential) and tolerance cost function for a normal process which provides a tailored way of incorporating the loss and tolerance cost in capability analysis. Next, we estimate the proposed PCI C pmc ′ when the process follows the normal distribution using six classical methods of estimation and we compare the performance of the considered methods of estimation in terms of their mean squared errors through simulation study. Besides, five bootstrap methods are employed for constructing the confidence intervals for the index C pmc ′ . The performance of the bootstrap confidence intervals (BCIs) are compared in terms of average width and coverage probabilities using Monte Carlo simulation. Finally, for illustrating the effectiveness of the proposed index and methods of estimation and BCIs, two real data sets from electronic industries are re-analyzed.
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More From: Communications in Statistics: Case Studies, Data Analysis and Applications
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