A Bayesian approach on monitoring process capability

Abstract

The generalized process incapability index C pp has been developed in the manufacturing industry to provide numerical measures on evaluating process performance. Contributions on the estimated incapability index C pp in existing quality assurance and statistical literature are almost from the frequentist point of view. In this paper, a Bayesian approach is developed under a non-informative prior to obtain the interval estimation for the generalized process incapability index C pp . Useful maximum values required to ensure the posterior probability reaching a certain desirable level based on C pp are tabulated. A Bayesian procedure for judging whether the process satisfies the preset quality reliability requirement is proposed. A practical example is also presented to illustrate how the proposed procedure may be applied.