Bayesian approach for measuring EEPROM process capability based on the one-sided indices CPU and CPL

Abstract

The purpose of process capability analysis is to provide numerical measures on whether a process is capable of reproducing items meeting the manufacturing specifications. Capability analyses have received consider- able recent research attention and increased usage in process assessments and purchasing decisions. Most ex- isting research works on capability analysis focus on estimating and testing process capability based on the tra- ditional distribution frequency approach. In this paper, we propose a Bayesian approach based on the indices CPU and CPL to measure EEPROM process capability, in which the specifications are one-sided rather than two-sided. We obtain the credible intervals of CPU and CPL and develop a Bayesian procedure for capability testing. The posterior probability p, for which the process under investigation is capable, is derived. The credible interval is a Bayesian analog of the classical lower confidence interval. A process satisfies the manufacturing capability requirements ifall the points in the credible interval are greater than the pre- specified capability level w. To make this Bayesian pro- cedure practical for in-plant applications, a real example of an EEPROM manufacturing process is investigated, demonstrating how the Bayesian procedure can be applied to actual data collected in the factories.