Design of SkSP-R Plan for Popular Statistical Distributions

The design of a Skip-lot sampling plan of type SkSP-R is presented for time truncated life test for the Weibull, Exponentiated Weibull, and Birnbaum-Saunders lifetime distributions. The plan parameters of the SkSP-R plan under these three distributions are determined through a nonlinear optimization problem. Tables are also constructed for each distribution. The advantages of the proposed plan over the existing sampling schemes are discussed. Application of the proposed plan is explained with the help of an example. The Birnbaum-Saunders distribution is economically superior to other two distributions in terms of minimum average sample number.

Inspection plan for COVID-19 patients for Weibull distribution using repetitive sampling under indeterminacy

Background This research work is elaborated investigation of COVID-19 data for Weibull distribution under indeterminacy using time truncated repetitive sampling plan. The proposed design parameters like sample size, acceptance sample number and rejection sample number are obtained for known indeterminacy parameter. Methods The plan parameters and corresponding tables are developed for specified indeterminacy parametric values. The conclusion from the outcome of the proposed design is that when indeterminacy values increase the average sample number (ASN) reduces. Results The proposed repetitive sampling plan methodology application is given using COVID-19 data belong to Italy. The efficiency of the proposed sampling plan is compared with the existing sampling plans. Conclusions Using the tables and COVID-19 data illustration, it is concluded that the proposed plan required a smaller sample size as examined with the available sampling plans in the literature.

A Two-stage Group Sampling Plan Based on Truncated Life Tests for an Odd Generalized Exponential Log-logistic Distribution

In this article, a time truncated life test based on two-stage group acceptance sampling plan is proposed for lifetime of an item follows odd generalized exponential log-logistic distribution (OGELLD). The ability about the lot acceptance can be made in the first or second stage according to the number of failures from each group. The optimal parameters for the proposed plan are determined such that both producer’s as well as consumer’s risks are contented simultaneously for the specified unreliability when group size and test duration are specified. The efficiency of the proposed sampling plan is evaluated in terms of average sample number with the existing sampling plan. The results are explained with the help of industrial example. Using exploratory data analysis and then goodness-of-fit, we show a rough indication of the goodness of fit for our model by plotting the superimposed for the data shows that the OGELLD is a good fit and also it is emphasized with Q-Q plot, displayed in Fig. 1. We observed from the tables / results that the number of groups required decrease as the group size increases from and also the ASN increases marginally, sample size decreases as the group size increases, which indicates that a larger group size may be more economical and it reduces the experimental time and cost. We proposed two-stage group acceptance sampling plan, since it performs much better in terms of the average sample number (ASN) and the operating characteristics than in single-stage group acceptance sampling plan. The advantage of two stage group sampling plan is that it reduces the average sample number (ASN) as compared to the GASP.

Design of SkSP-R Variables Sampling Plans

In this paper, we present the designing of the skip-lot sampling plan including the re-inspection called SkSP-R. The plan parameters of the proposed plan are determined through a nonlinear optimization problem by minimizing the average sample number satisfying both the producer's risk and the consumer's risks. The proposed plan is shown to perform better than the existing sampling plans in terms of the average sample number. The application of the proposed plan is explained with the help of illustrative examples.