Affiliation:
1. Division of Statistics, Northern Illinois University, De Kalb, IL 60115, USA
Abstract
The supplier selection problem consists of selecting the best of several possible suppliers for a product. The selection criteria, in the absence of considerations such as cost, are based on a quality metric such as the capability of the supplier's manufacturing process. Because quality metrics are estimated based on sample process data, the inherent variability in the estimates must be accounted for when selecting the best supplier. In this paper we consider a methodology based on the bootstrap that assigns confidence levels to each of the suppliers. These confidence levels are designed to reflect the amount of confidence we have that the supplier actually has the best quality metric, conditional on the observed samples. The methodology is demonstrated using two examples.
Publisher
World Scientific Pub Co Pte Lt
Subject
Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Energy Engineering and Power Technology,Aerospace Engineering,Safety, Risk, Reliability and Quality,Nuclear Energy and Engineering,General Computer Science
Cited by
8 articles.
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