Design of Multiple Deferred State Repetitive Group Sampling Plans for Life Tests based on Generalized Gamma Distribution

Abstract

Reliability sampling plans is a procedure to determine the acceptance or non-acceptance of the lot(s) of finished products by performing tests on the sampled items. Lifetime of individual items is a quality characteristic that can be treated as a continuous random variable and can be modeled by an appropriate continuous probability distribution. In this article, Multiple Deferred State Repetitive Group Sampling (MDSRGS) Plans for life tests under hybrid censoring with a provision to draw a random sample and to admit a maximum of one failure in the sample is formulated assuming that the lifetime random variable follows a Generalized Gamma (GG) distribution. A methodical procedure for the selection of the plan parameters using mean life criterion with the desired discrimination protecting the interests of the producer and the consumer in terms of the acceptable mean life and unacceptable mean life is evolved.

Keywords:

• acceptable mean life
• Average Sample Numbers (ASN)
• Generalized Gamma (GG) distribution
• hybrid censoring
• MDSRGS plan

Acknowledgments

The author is grateful to the Editor and Reviewers who have made significant suggestions for the improvements in the substance of the paper. The author is grateful to Vellore Institute of Technology, Vellore, India for providing necessary facilities to carry out this research work.

Additional information

Notes on contributors

K. Sathya Narayana Sharma

Dr. K. Sathya Narayana Sharma is currently working as an Assistant Professor, Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore, INDIA. He received the Master of Sciences in Statistics in 2014, Master of Philosophy in Statistics degree from Periyar University in 2016 and Doctorate of Philosophy (Ph.D) in Statistics degree from the Bharathiar University in 2020. He has published several papers in various International Journals and Conferences. His research interests include Statistical Quality Control and Reliability Sampling.