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Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution

Author

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  • Srinivasa Rao Gadde
  • Arnold K. Fulment
  • Josephat K. Peter
  • Tao Zhou

Abstract

The proposed sampling plan in this article is referred to as multiple dependent state (MDS) sampling plans, for rejecting a lot based on properties of the current and preceding lot sampled. The median life of the product for the proposed sampling plan is assured based on a time-truncated life test, when a lifetime of the product follows exponentiated Weibull distribution (EWD). For the proposed plan, optimal parameters such as the number of preceding lots required for deciding whether to accept or reject the current lot, sample size, and rejection and acceptance numbers are obtained by the approach of two points on the operating characteristic curve (OC curve). Tables are constructed for various combinations of consumer and producer’s risks for various shape parameters. The proposed MDS sampling plan for EWD is demonstrated using the coronavirus (COVID-19) outbreak in China. The performance of the proposed sampling plan is compared with the existing single-sampling plan (SSP) when the quality of the product follows EWD.

Suggested Citation

  • Srinivasa Rao Gadde & Arnold K. Fulment & Josephat K. Peter & Tao Zhou, 2021. "Design of Multiple Dependent State Sampling Plan Application for COVID-19 Data Using Exponentiated Weibull Distribution," Complexity, Hindawi, vol. 2021, pages 1-10, October.
    • Handle: RePEc:hin:complx:2795078
    DOI: 10.1155/2021/2795078
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