Group acceptance sampling plan based on truncated life tests for the Kumaraswamy Bell–Rayleigh distribution

Abstract

This article is focusing on a group acceptance sampling plan for the Kumaraswamy Bell–Rayleigh distribution based on truncated life tests. For a specified group, the mean ratio as a quality measure is being used to determine the minimum number of lots and the acceptance number needed to satisfy a particular consumer’s and producer’s risk which is assisting in the determination of the test termination time and required number of testers. In addition, simulation studies to demonstrate the stability and accuracy of the estimates are being carrying out together with the hypothetical illustration of the Group acceptance sampling plan based on the Kumaraswamy Bell–Rayleigh model. The values of the operating characteristic function are being obtained using various quality levels. The new distribution utility is being justifying with data on the COVID-19 death rate in Angola and the supply of protein in Afghanistan. Preliminary data diagnostics reveal that the two data sets are quasi-normal with only a data point causing the first data to deviate from normality. The results reveal that the proposed model fits the data better than the other fitted models and is also preferred in the estimation of parameters. In addition, from the life example, the applicability of the proposed group acceptance sampling plan under the new model was showcased.