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 considerable recent research attention and increased usage in process assessments and purchasing decisions. Most existing research works on capability analysis focus on estimating and testing process capability based on the traditional 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 if all the points in the credible interval are greater than the pre-specified capability level w. To make this Bayesian procedure 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.
|Number of pages||10|
|Journal||International Journal of Advanced Manufacturing Technology|
|State||Published - 1 Nov 2006|
- Bayesian approach
- Credible interval
- Posterior probability
- Process capability indices