Mixed Acceptance Sampling Plans for Product Inspection Using Process Capability Index

ABSTRACT

In this article, a mixed acceptance sampling plan, which is the combination of an attribute plan and a variable plan based on , is proposed when the quality characteristic follows the normal distribution. The plan parameters are determined using a nonlinear optimization method such that producer's risk and consumer's risk are satisfied simultaneously for given values of acceptable quality level and limiting quality level. Symmetric and asymmetric cases are considered to design the proposed plan. The performance of the proposed plan over the attribute and variable sampling plans is discussed. Tables of plan parameters and examples are given to illustrate the plan developed here.

KEYWORDS:

• normal distribution
• process capability index
• producer's risk
• consumer's risk
• mixed sampling

ACKNOWLEDGMENTS

The authors are thankful to the reviewer and Associate Editor for their valuable suggestions to improve the quality of the article.

Additional information

Funding

The work by Chi-Hyuck Jun was funded by the Ministry of Education, Science, and Technology (2010-0028229) and by the Korea Ministry of Environment (MOE) as “Ecodesign Human Resource Development Project.”

Notes on contributors

Muhammad Aslam

Dr. Muhammad Aslam did his M.Sc. in Statistics (2004) from GC University Lahore with Chief Minister of the Punjab merit scholarship, M. Phil in Statistics (2006) from GC University Lahore with the Governor of the Punjab merit scholarship, and Ph.D. in Statistics (2010) from National College of Business Administration & Economics Lahore under the kind supervision of Prof. Dr. Munir Ahmad. He worked as a lecturer of Statistics in Edge College System International from 2003–2006. He also worked as Research Assistant in the Department of Statistics, GC University Lahore from 2006 to 2008. Then he joined the Forman Christian College University as a lecturer in August 2009. He worked as Assistant Professor in the same University from June 2010 to April 2012. Currently, he is working as an Associate Professor of Statistics in the same department. He has published more than 115 research papers in national and international journals including for example, Journal of Applied Statistics, Information Sciences, European Journal of Operation Research, Journal of the Operational Research Society, Applied Mathematical Modeling, International Journal of Advanced Manufacturer Technology, Communications in Statistics, Journal of Testing and Evaluation and Pakistan Journal of Statistics. He is the author of one book published in Germany. He is also HEC approved PhD supervisor since 2011. He reviewed more than 50 research papers for various well reputed international journals. He received meritorious services award in research from National College of Business Administration & Economics Lahore in 2011. He received Research Productivity Award for the year 2012 by Pakistan Council for Science and Technology. His name Listed at 2nd Position among Statistician in the Directory of Productivity Scientists of Pakistan 2013. He is the member of editorial board of Electronic Journal of Applied Statistical Analysis and Pakistan Journal of Commence and Social sciences. He is also member of Islamic Countries Society of Statistical Sciences. His areas of interest include reliability, decision trees, Industrial Statistics, acceptance sampling, rank set sampling and applied Statistics.

Chien-Wei Wu

Chien-Wei Wu is currently a Professor in the Department of Industrial Engineering and Engineering Management at National Tsing Hua University (NTHU), Taiwan. He received his Ph.D. degree in Industrial Engineering and Management from National Chiao Tung University in 2004 and the M.S. degree in Statistics from National Tsing Hua University in 2002. He worked for National Taiwan University of Science and Technology and Feng Chia University before he joined NTHU. He is also 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.

Muhammad Azam

Muhammad Azam received the Ph.D. degree in Statistics from the University of Innsbruck, Austria in 2010. He joined the Department of Statistics at the Forman Christian College University Lahore in 2010, where he now holds the position of Associate Professor. His research interests include topics related to Survey Sampling, Quality Control, Decision Trees and Ensemble Classifiers.

Chi-Hyuck Jun

Chi-Hyuck Jun is a professor in Department of Industrial and Management Engineering, POSTECH. He received B.S. in mineral and petroleum engineering from Seoul National University, M.S. in Industrial Engineering KAIST and Ph.D. in Operations Research from University of California, Berkeley. Since 1987 he has been with the Department of Industrial and Management Engineering, POSTECH. He is interested in data mining and reliability/quality.