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An Application of Fuzzy-AHP Approach to a Product Variety Management Problem

Thanathorn Karot 1, Choosak Pornsing 1, Tongtang Tonglim 2, and Peerapop Jomtong 3
1. Engineering Management Research Unit, Department of Industrial Engineering and Management, Faculty of Engineering and Industrial Technology, Silpakorn University, Nakhon Pathom 73000, Thailand
2. Faculty of Science and Technology, Muban Chombueng Rajabhat University, Ratchaburi, Thainland
3. Department of Biomedical Engineering, Faculty of Biomedical Science, Christian University of Thailand, Nakhon Pathom, Thailand
Abstract—Due to the proliferation of mass customization, firms are struggling to explore the balance between the number of product variants and operation performance. In this article, a soft approach of the decision making on product variety management is proposed. A fuzzy-analytic hierarchy process (Fuzzy-AHP) is a main tool; however, we also introduce an applicable procedure in which consists of other decision tools, such as, group technology, activity-based costing analysis, and brainstorming in order to make this research project practical. A sample automotive part manufacturer is the case experiment. It faced with more than 1,200 SKUs and deteriorated the performance of manufacturing system. However, there were arguments from different perspectives from different managers about discontinuing products. The proposed method compromised all crisp information from relative departments and all numerical information from factory’s activities. The results show that the sample factory could reduce the product variety by 311 SKUs, about 26%. This makes the company more efficiency by reducing setup cost, material handling cost, warehouse space, and all other relevant operations. 

Index Terms—analytic hierarchy process, product variety, fuzzy, soft approach, decision making

Cite: Thanathorn Karot, Choosak Pornsing, Tongtang Tonglim, and Peerapop Jomtong, "An Application of Fuzzy-AHP Approach to a Product Variety Management Problem," Journal of Advanced Management Science, Vol. 8, No. 1, pp. 22-27, March 2020. doi: 10.18178/joams.8.1.22-27
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