Applications of process capability indices for suppliers selection problems using generalized confidence interval

Abstract

Abstract In process capability indices, the generalized confidence interval (GCI) method has been used many times in several research articles. In this article, we have considered the supplier’s selection problems by using the GCI of difference between two process capability indices . We have considered two classical methods of estimation, viz. maximum likelihood estimation (MLE), and maximum product spacing estimation (MPSE) to estimate . By using Monte Carlo simulation, we have obtained the biases and corresponding mean squared errors (MSEs) of . Here, we also find the lower confidence limit (L), upper confidence limit (U), and their corresponding average width (AW) for both classical methods MLE and MPSE. Three real data sets have been reanalyzed to illustrate the methodology of the supplier’s selection problem by utilizing the generalized confidence interval method.