A Bayesian approach to obtain a lower bound for the C-pm capability index

Abstract

The Taguchi capability index C-pm, which incorporates the departure of the process mean from the target value, has been proposed to the manufacturing industry for measuring manufacturing capability. A Bayesian procedure has been considered for testing process performance assuming mu = T, which was generalized without assuming mu = T. Statistical properties of the natural estimator of the index C-pm for normal processes have been investigated extensively. However, the investigation was restricted to processes with symmetric tolerances. Recently, a generalized C-pm, referred to as C-pm", was proposed to cover processes with asymmetric tolerances. Under the normality assumption, the statistical properties of the estimated C-pm" including the exact sampling distribution, the rth moment, expected value, variance, and the mean-squared error were obtained. In this paper, we use a Bayesian approach to obtain the interval estimation for the generalized Taguchi capability index C-pm" Consequently, the manufacturing capability testing can be performed for quality assurance. Copyright (c) 2005 John Wiley & Sons, Ltd.