Repetitive inspection scheme based on the run length of test results: A Markov chain Monte Carlo approach

Abstract

We propose a repetitive inspection plan that is based on the run-length of positive and negative test results. In a numerical analysis, we show that the new inspection plan outperforms previous ones in terms of the expected total cost as well as the average outgoing quality. The model parameters are often assumed to be known in advance, but we propose the use of a Bayesian method to estimate the point and interval estimates of the unknown parameters. We show that computational difficulties with prior distributions of the three parameters can be easily overcome with an appropriate MCMC method.

Keywords:

• inspection
• product quality
• reliability
• MCMC estimation
• simulation
• Markov chain model

Acknowledgments

We’d like to express our sincere gratitude to two anonymous referees for their thorough and valuable reviews that helped us improve the original manuscript significantly.

Additional information

Funding

The first author also would like to offer his appreciation for the financial support from Cherie H. Flores Endowed Chair of MBA Studies at Louisiana State University.

Notes on contributors

Young H. Chun

Young H. Chun is Professor of Decision Science and Cherie H. Flores Endowed Chair of MBA Studies at E. J. Ourso College, Louisiana State University. He received his PhD from Krannert Graduate School of Management at Purdue University in USA in 1990. His current research interests are in quality control and reliability, statistical decision analysis, and warranty analysis. His work has been published in various journals such as Quality Engineering, Operations Research, Decision Sciences, Journal of the Operational Research Society, European Journal of Operational Research, Naval Research Logistics, IIE Transactions, IEEE Transactions on Engineering Management, Journal of Quality Technology, and American Statistician.

Seong-Jong Joo

Seong-Jong Joo is a Professor of Logistics & Supply Chain Management in the Department of Operational Sciences at the Air Force Institute of Technology. He teaches graduate courses in Logistics and Supply Chain Management. Before returning to academia, he had served in the Republic of Korea Air Force (ROKAF) for 21 years as a Supply Officer and retired honorably with the final rank of Lieutenant Colonel. During his service with the ROKAF, he gained practical experience in a variety of areas related to Logistics and Supply Chain Management such as purchasing and supply management, warehousing and inventory management, and logistics and transportation management.