Scheming of reliability sampling plans with some lifetime distributions based on percentiles estimation using intervened Poisson characteristics

Abstract

Abstract In industry, the practice of determining the performance of a product by intervening with the normal working conditions of the manufacturing process is an acceptable method. When reliability is a key quality factor, the reliability single sampling plan is generally used to optimise sample size and estimate time characteristics. The application of Intervened Poisson Distribution (IPD) and some of the lifetime distributions are used in this article to implement a reliability sampling plan. The IPD can be used as a model for counting the defective items in an appropriate situation and the defectiveness will be determined with the help of lifetime distributions. The minimum sample size required to accept a lot and the estimation of the true percentile time of the accepted lots according to the magnitude of the intervention parameter can be found using IPD associated with the Rayleigh Distribution (RD), Exponentiated Rayleigh Distribution (ERD) and Inverse Rayleigh Distribution (IRD). The minimum sample size is necessary to ensure the specified life percentile is obtained under a consumer risk. The operating characteristic (OC) values and estimated percentile time of an accepted lot are presented.