Acceptance sampling plans under two-parameter Quasi Shanker distribution assuring mean life with an application to manufacturing data

Author:

Al-Omari Amer Ibrahim1ORCID,Almanjahie Ibrahim M23ORCID,Dar Javid Gani4

Affiliation:

1. Department of Mathematics, Faculty of Science, Al al-Bayt University, Mafraq, Jordan

2. Department of Mathematics, College of Science, King Khalid University, Abha, South Region, Saudi Arabia

3. Statistical Research and Studies Support Unit, King Khalid University, Abha, Saudi Arabia

4. Department of Mathematical Sciences, Islamic University of Science and Technology, Awantipora, Kashmir, India

Abstract

The acceptance sampling plan (ASP) is a statistical tool used in industry for quality control to determine the quality of products by selecting a specified number for testing in order to accept or reject the lot. The main objective is to develop a new ASP based on truncated life tests assuming that the lifetime follows the two parameters Quasi Shanker distribution, since this distribution showed its superiority in providing a better model for some applications than the exponential distribution. The ASP steps are carried out to find the minimum sample sizes needed to assert the certain life mean that are calculated under a given customer’s risk. The operating characteristic values of the sampling plan and the producer risk values are obtained. The efficiency of the suggested plans is analyzed based on real data that is fitted to the Quasi Shanker distribution. For various values of the Quasi Shanker distribution parameters, numerical examples are presented for illustrative purposes. The results indicate that the suggested ASP provides smaller sample sizes than other competitors considered in this study. The suggested ASP has been found to provide a substantial sampling economy in terms of reducing the sample. Hence, it is recommended that the ASP can be used in industry and for future research works as double and group ASP.

Funder

King Khalid University

Publisher

SAGE Publications

Subject

Multidisciplinary

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