An integrated operating mechanism for lot sentencing based on process yield

ABSTRACT

A flexible sampling policy integrated with the consideration of past records is discussed in this paper for the quality evaluation of submission based on process yield. Lot sentencing plays the main role in buyer-seller business contracts for deliveries. A continuous partnership between the vendor and buyer can help in maintaining historically traceable results whereby the recording information is considered valuable. Hence, we propose a new sampling strategy with an integrated operating mechanism that considers the preceding inspection results to lessen the required average sample number based on process yield. Compared with the conventional methods, the proposed modified sampling strategy has the advantage of having a small number of samples for inspection while providing desirable protection under the same quality requirements and tolerable sampling risks. An application taken from the contact lens industry is presented to demonstrate the practicability of this research.

KEYWORDS:

• Lot sentencing
• acceptance sampling plan
• discriminatory power
• OC curve
• average sample number

Disclosure of potential conflicts of interest

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was partially supported by the Ministry of Science and Technology of Taiwan under Grant No. MOST 108-2218-E-167-008-MY2 .

Notes on contributors

Shih-Wen Liu

Shih-Wen Liu is currently an Assistant Professor in the College of Management at National Chin-Yi University of Technology (NCUT), Taiwan. Dr. Liu received his Ph.D. degree in Industrial Management from National Taiwan University of Science and Technology (NTUST) in 2016. His research interests include quality engineering and management, statistical process control, process capability analysis, applied statistics and data analysis.

Chien-Wei Wu

Chien-Wei Wu is currently a distinguished Professor in the Department of Industrial Engineering and Engineering Management at National Tsing Hua University (NTHU), Taiwan. Dr. Wu received his Ph.D. degree in Industrial Engineering and Management with Outstanding Ph.D Student Award from National Chiao Tung University in 2004, the M.S. degree in Statistics from National Tsing Hua University in 2002 and the B.S. degree in Applied Mathematics with the Phi Tao Phi Honor from National Chung Hsing University (NCHU) in 2000. He worked for National Taiwan University of Science and Technology (NTUST) and Feng Chia University (FCU) before he joined NTHU. Dr. Wu has received Dr. Ta-You Wu Memorial Award (Outstanding Young Researcher Award) from National Science Council (NSC) in 2011 and Outstanding Young Industrial Engineer Award from Chinese Institute of Industrial Engineers (CIIE) in 2011, Excellent Research Award in 2011 and Excellent Teaching Award in 2012 from NTUST. He is also serving as one of Editors-in-Chief of Quality Technology and Quantitative Management (QTQM) (SCI-E indexed) and editorial board members for various international journals. His research interests include quality engineering and management, statistical process control, process capability analysis, applied statistics and data analysis.

Zih-Huei Wang

Zih-Huei Wang is an assistant professor in Department of Industrial Engineering and Systems Management at Feng Chia University in Taiwan. Dr. Wang received PhD degree in Industrial Engineering from National Tsing Hua University in 2018. Her research interest mainly focuses on quality engineering and management, process capability analysis, design of experiment and data analysis. She has published some journals and conference papers in recent years. During 2017, she had been a visiting scholar at Georgia Tech in Atlanta and cooperated with Piedmont Heart Institute on the medical image analysis project, and also published two conference papers, one conference poster, and one book chapter in the aforementioned field.