A Study of Multicriteria Decision Making for Supplier Selection in Automotive Industry | Zendy

Nadia Jamil | Zendy; Rosli Besar | Zendy; Hock Kheng Sim | Zendy

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A Study of Multicriteria Decision Making for Supplier Selection in Automotive Industry

Author(s) -

Nadia Jamil,

Rosli Besar,

Hock Kheng Sim

Publication year - 2013

Publication title -

journal of industrial engineering

Language(s) - English

Resource type - Journals

eISSN - 2314-4890

pISSN - 2314-4882

DOI - 10.1155/2013/841584

Subject(s) - topsis , ideal solution , analytic hierarchy process , ranking (information retrieval) , multiple criteria decision analysis , automotive industry , selection (genetic algorithm) , fuzzy logic , supply chain , operations research , computer science , supply chain management , supplier relationship management , process (computing) , ideal (ethics) , engineering , artificial intelligence , business , marketing , philosophy , physics , epistemology , thermodynamics , aerospace engineering , operating system

This paper is designed to present the effectiveness of group multicriteria decision making in automotive manufacturing company focusing on the selection of suppliers in Malaysia. The process of selecting suppliers is one of the most critical and challenging endeavor in any supply chain management. There are five decision making tools being analyzed in this study, namely, analytical hierarchy process (AHP), fuzzy analytical hierarchy process (FAHP), technique for order performance by similarity to ideal solution (TOPSIS), fuzzy technique for order performance by similarity to ideal solution (FTOPSIS), and fuzzy analytical hierarchy process integrated with fuzzy technique for order performance by similarity to ideal solution (FAHPiFTOPSIS). The scores of ranking among the suppliers in each MCDM tools (AHP, FAHP, TOPSIS, FTOPSIS, and FAHPiFTOPSIS) show significantly comparable variation. Scores of the best supplier is then compared to the lowest supplier for all MCDM tools whereby this reflects that the highest percentage goes to TOPSIS with scoring of 79.37%. On the contrary, FAHPiFTOPSIS demonstrated the lowest score variation of 22.42% which indicates that FAHPiFTOPSIS is able to eliminate biasness in supplier selection process.

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