Determination and economic design of repetitive group sampling plan under two parameter Lindley distribution

ABSTRACT

A designing procedure of repetitive group sampling plan for assuring mean life under a two-parameter Lindley distribution is proposed, and the optimization model is developed for finding the optimal plan parameters such that the demands of both supplier and buyer are satisfied simultaneously. A real-time data set of ball bearings is used to explain the application of the proposed plan. A comparison between the proposed plan and the single sampling plan is done to reveal the better performance of the proposed plan based on operating characteristic function and average sample number. Applying the proposed plan to provide lifetime assurance reduces the inspection effort and related costs. We discuss the design of the proposed plan with an economic aspect. In addition, the sensitivity of the optimal sampling plans concerning the failure probability and cost parameters is analyzed. Finally, it is evident from the study that the proposed plan will be preferable to a single sampling plan for providing quality assurance with a minimum cost of the inspection.

KEYWORDS:

• Acceptance sampling
• discriminating power
• lifetime model
• time truncated life test

Acknowledgments

The authors would like to thank the anonymous reviewers, the Associate Editor, and the Editor for their insightful comments and valuable suggestions that led to improving the presentation of the manuscript. This research was supported by the Department of Science and Technology-Science and Engineering Research Board (DST-SERB) of India through the project (CRG/2020/005078).

Disclosure statement

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

Additional information

Funding

The work was supported by the Science and Engineering Research Board, India .

Notes on contributors

P. Jeyadurga

P. Jeyadurga is an Assistant Professor in the Department of Mathematics, Thiagarajar College of Engineering, Madurai, India. She completed her M. Sc. in Mathematics at Madurai Kamaraj University and received her Ph. D. degree from Kalasalingam Academy of Research and Education. Her areas of interest are acceptance sampling, control charts. She has published her research work in the field of sampling plans and control chart.

S. Balamurali

S. Balamurali is a Professor of Statistics at Kalasalingam University. He earned his M. Sc. and Ph. D. degrees from Bharathiyar University, India. His research interests include statistical process control, acceptance sampling, analysis of means and data mining. He has published his research papers in various well reputed statistics and engineering journals including IEEE Transactions on Reliability, European Journal of Operational Research, Journal of Applied Statistics, Applied Stochastic Models in Business and Industry, The International Journal of Advanced Manufacturing Technology, Journal of Testing and Evaluation, etc.