Generalized multiple dependent state sampling plans for coefficient of variation

Abstract

Sampling plans using the coefficient of variation (CV) attract increasing attention by many authors in the literature due to its importance to measure the product quality. A generalized multiple dependent state (GMDS) sampling plan for accepting a lot is proposed based on the coefficient of variation when a quality characteristic comes from a normal distribution. The optimal plan parameters of the proposed plan are solved by a nonlinear optimization model, which minimizes the sample size required for inspection while satisfying the given producer’s risk and the consumer’s risk at the same time. A comparative study of the proposed GMDS sampling plan over the two existing sampling plans is considered. A real example is given to demonstrate the proposed plan.

Keywords:

• Generalized multiple dependent state sampling plan
• coefficient of variation
• normal distribution
• non-central t distribution
• producer’s risk
• consumer’s risk

Acknowledgements

The authors are deeply thankful to the editor and reviewers for their valuable suggestions to improve the quality of the paper.

Additional information

Funding

The work by Chi-Hyuck Jun was also supported by Korea Institute for Advancement of Technology (KIAT) grant (# SBS19BR1) funded by the Korea Government (MOTIE).