Abstract
Selecting the right supplier for a right product is a challenging problem in any industry. Especially in auto-mobile industry the problem becomes much more complex as there are many automobile components and with each component having many parts. Key Performance indicators which are widely used across the automobile industry are proposed for measuring and monitoring the supplier performance. Experts are used to provide their feedback on the Key Performance indicators. Experts are evaluated on Experience, Knowledge and Leadership skills. The reliance of experts to provide their ratings (pair-wise comparison ratings between KPIs) has been in practice for quite some time. However, the ratings differ from expert to expert depending on their knowledge, experience, relevance and leadership skills. An average rating would not give a right solution to the problem. In this paper an AI based Fuzzy AHP methodology is proposed for computing the weights of the experts. These weightages will be used subsequently by automobile companies in computing the weights of the Key performance indicators. Using the hybrid of expert and criteria weights computed and the ratings of the supplier on each of the seven KPIs, a weighted score is computed and top ten suppliers are identified at the part level or at the component level for the automobile industry.
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