نوع مقاله : یادداشت فنی
نویسندگان
1 دانشکده‌ی مهندسی صنایع، دانشگاه علم و فنّاوری مازندران
2 دانشکده‌ی مهندسی صنایع، پردیس دانشکده‌های فنی، دانشگاه تهران
3 دانشکده‌ی مهندسی صنایع، دانشگاه علم و صنعت ایران
چکیده
کلیدواژه‌ها
عنوان مقاله [English]
نویسندگان [English]
Supply chain risk management has become an essential issue for supply chain management. Companies must focus not only on the efficiency of supply chain, but also on manageability of its risks. There are two types of supply chain risks: operational and disruptional risks. Operational risk is associated with the uncertainty of a process such as customer demand, amount of supply, and cost fluctuations. Disruptional risk encompasses natural and man-made disasters, such as earthquakes, floods, hurricanes, terrorist attacks, financial crises, or labor strikes. If an unanticipated event occurs, all of the supply chain members will be affected and the result will cause significant loss. Supplier risk is one the of the supply chain risks that could be the source of other supply chain risks and leads to the inability of the supply chain to meet the customers demand. The Supplier selection process is one of the most important components of production and logistics management for many companies. Selection of a wrong supplier could be enough to weaken the companys financial and operational position. Selecting the right suppliers significantly reduces purchasing costs, improves competitiveness in the market and enhances end user satisfaction. This research proposes a hybrid model of interval valued ANP, interval valued fuzzy FMEA and interval valued fuzzy TOPSIS for the selection of the supplier with the lowest risk in the supply chain. This method applies the interval valued fuzzy ANP to determine the weight of each criterion and sub-criterion, uses interval valued fuzzy FMEA to rank the risk factors related to each supplier and interval valued fuzzy TOPSIS for the final supplier ranking. In addition, we applied linguistic variables to the parameter in which these variables are expressed as triangular interval-valued fuzzy numbers. A steel company is then studied to validate this model. The result shows that this company can categorize its suppliers more effectively and can select a low-risk supply chain partner at the same time.
کلیدواژه‌ها [English]
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