A variables multiple dependent state sampling plan based on a one-sided capability index

ABSTRACT

Acceptance sampling plan has been considered as one of most practical tools for quality assurance applications. While various types of acceptance sampling plans have been developed for different purposes, single acceptance sampling plan is the most popular because it is simple to administrate. However, a new concept called multiple dependent state sampling has gained the attention of scholars in recent years. The underlying principle is that the acceptance of a submitted lot should not only depend on the quality of the current lot but also consider the quality of the preceding lots. This research develops a variables multiple dependent state sampling plan (VMDSSP) for unilateral specification limit based on a one-sided capability index. The operating characteristic (OC) curve is prepared based on the exact sampling distribution. The plan parameters are determined by minimizing the average sample number while satisfying the quality levels demanded by both the producer and the consumer. The performance of the proposed plan is compared with the traditional variables single sampling plan (VSSP) and is examined in a case study.

KEYWORDS:

• acceptance sampling
• operating characteristic curve
• process capability index
• process yield

About the authors

Chien-Wei Wu is currently a Professor in the Department of Industrial Engineering and Engineering Management at National Tsing Hua University (NTHU), Taiwan. Dr. Wu received his Ph.D. in Industrial Engineering and Management with Outstanding Ph.D. Student Award from National Chiao Tung University in 2004 and a M.S. degree in Statistics from National Tsing Hua University in 2002. He is serving as one of Editors-in-Chief of Quality Technology and Quantitative Management (QTQM) and editorial board members for various International journals. His research interests include quality engineering and management, statistical process control, process capability analysis, and data analysis.

Amy H. I. Lee is a Professor in the Department of Technology Management, Department of Industrial Management, and Ph.D. Program of Technology Management at Chung Hua University, Taiwan. Dr. Lee received an MBA from the University of British Columbia, Canada, in 1993 and a Ph.D. in Industrial Engineering and Management from the National Chiao Tung University, Taiwan, in 2004. Her research interests include performance evaluation, new product development, supply chain management, and production management.

Chih-Chieh Chang Chien received his Master's degree from the Department of Industrial Engineering and Engineering Management at National Tsing Hua University (NTHU), Taiwan, in 2015. His specific research interests include process capability analysis, quality measurement, and statistical analysis.

Acknowledgments

The authors would like to thank the Associate Editor and two anonymous referees for their helpful comments and careful readings, which significantly improved the presentation of this article.

Funding

This work was partially supported by the Ministry of Science and Technology of Taiwan under Grant No. MOST 103-2221-E-007-103-MY3.