摘要
The quality of products manufactured or procured by organizations is an important aspect of their survival in the global market. The quality control processes put in place by organizations can be resource-intensive but substantial savings can be realized by using acceptance sampling in conjunction with batch testing. This paper considers the batch testing model based on the quality control process where batches that test positive are re-tested. The results show that re-testing greatly improves the efficiency over one stage batch testing based on quality control. This is observed using Asymptotic Relative Efficiency (ARE), where for values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;"> computed ARE > 1 implying that our estimator has a smaller variance than the one-stage batch testing. Also, it was found that the model is more efficient than the classical two-stage batch testing for relatively high values of proportion.
The quality of products manufactured or procured by organizations is an important aspect of their survival in the global market. The quality control processes put in place by organizations can be resource-intensive but substantial savings can be realized by using acceptance sampling in conjunction with batch testing. This paper considers the batch testing model based on the quality control process where batches that test positive are re-tested. The results show that re-testing greatly improves the efficiency over one stage batch testing based on quality control. This is observed using Asymptotic Relative Efficiency (ARE), where for values of </span><i><span style="font-family:Verdana;">p</span></i><span style="font-family:Verdana;"> computed ARE > 1 implying that our estimator has a smaller variance than the one-stage batch testing. Also, it was found that the model is more efficient than the classical two-stage batch testing for relatively high values of proportion.
作者
Ronald Waliaula Wanyonyi
Olivia Wanjeri Mwangi
Charles Wambugu Mwangi
Ronald Waliaula Wanyonyi;Olivia Wanjeri Mwangi;Charles Wambugu Mwangi(Department of Mathematics, Egerton University, Njoro, Kenya;Data Science Institute, University of Delaware, Newark, DE, USA;Department of Mathematics and Actuarial, Kabarak University, Kabarak, Kenya)
