Abstract
ABSTRACT The process capability indices (PCIs) are frequently adopted to measure the performance of a process within the specifications. Although higher PCIs indicate higher process “quality,” yet it does not ascertain fewer rates of rejection. Thus, it is more appropriate to adopt a loss-based PCI for measuring the process capability. In this paper, our first objective is to introduce a new capability index called which is based on symmetric loss function for normal process which provides a tailored way of incorporating the loss in capability analysis. Next, we estimate the PCI when the process follows the normal distribution using method of moment (MOM) estimation and compare the performance of the MOM estimation in terms of their absolute biases and corresponding mean squared errors through simulation study in respect of sample sizes. Besides, generalized confidence interval (GCI) is employed for constructing the confidence intervals for the index . The performance of GCI is compared in terms of average widths and coverage probabilities using Monte Carlo simulation. Finally, for illustrating the effectiveness of the proposed method of estimation and GCI, three real data sets from electronic industries are analyzed.
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More From: Communications in Statistics: Case Studies, Data Analysis and Applications
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