Supplier selection using modified fuzzy AHP-based approach in manufacturing networks

Due to the economy recession all around the world, the performance of manufacturing industry has been significantly affected. The question of how to generate fast response to customers, maintain the high quality, accurate delivery rate and low risk become the crucial issue of keeping a company competitive. Supplier selection, one of the key factors for a successful production process has attracted more attention in the recent decade. This research aims to understand the supplier selection procedure in Small to Medium-sized Enterprises (SMEs) manufacturing networks. Statistical method Kernel density estimation is integrated with Fuzzy AHP for the first time to improve the accuracy for the evaluation of suppliers against quantitative criteria. Data and information are collected from a central company which coordinates manufacturing networks of SMEs as an industrial case study. As a result, the proposed statistical analysis method for supplier evaluation with respect to quantitative criteria could successfully assist decision makers and reduce the potential bias from a visual aspect in the decision making process.