رویکرد فازی AHP برای انتخاب عرضه کننده در یک شرکت ماشین لباسشویی

Supplier selection process has gained importance recently, since the cost of raw materials and component parts constitutes the main cost of a product and most of the firms have to spend considerable amount of their revenues on purchasing. Supplier selection is one of the most important decision making problems including both qualitative and quantitative factors to identify suppliers with the highest potential for meeting a firm’s needs consistently and at an acceptable cost. In this study, supplier selection problem of a well-known washing machine company in Turkey is investigated and a fuzzy analytic hierarchy process based methodology is used to select the best supplier firm providing the most customer satisfaction for the criteria determined. After the main attributes and sub-attributes for supplier selection are defined to design the hierarchy structure, the weights of them and alternatives are calculated using fuzzy analytic hierarchy process approach. The supplier with the highest priority weight is selected as the best supplier. Macros in MS Excel are written to calculate the priority weights of the alternatives based on the questionnaire forms used to facilitate comparisons of main attributes, sub-attributes and alternatives.

Increases and varieties of customer demands, advances of recent technologies in communication and information systems, competition in global environment, decreases in governmental regulations and increases in environmental consciousness have forced companies for focusing on supply chain management (Tracey & Tan, 2001). The “supply chain management” term defines the integration of activities to procure materials, transforms them into intermediate goods and final products, and delivers to customers. The supply chain consists of all links from suppliers to customers of a product. Goffin, Szwejczewski, and New (1997) have stated that supplier management is one of the key issues of supply chain management because the cost of raw materials and component parts constitutes the main cost of a product and most of the firms have to spend considerable amount of their sales revenues on purchasing. In most industries the cost of raw materials and component parts constitutes the main cost of a product, such that in some cases it can account for up to 70% (Ghobadian, Stainer, & Kiss, 1993). In high technology firms, purchased materials and services represent up to 80% of total product cost (Weber, Current, & Benton, 1991). Thus the purchasing department can play a key role in an organization’s efficiency and effectiveness since the department has a direct effect on cost reduction, profitability and flexibility of a company by selecting the right suppliers significantly reduces the purchasing costs and improves corporate competitiveness (Ghodsypour & O’Brien, 2001). Supplier selection is a multi-criteria problem which includes both qualitative and quantitative factors. In order to select the best suppliers it is necessary to make a trade off between these tangible and intangible factors some of which may conflict (Ghodsypour & O’Brien, 1998). The objective of supplier selection is to identify suppliers with the highest potential for meeting a firm’s needs consistently and at an acceptable cost. Selection is a broad comparison of suppliers using a common set of criteria and measures. However, the level of detail used for examining potential suppliers may vary depending on a firm’s needs. Although analytical hierarchy process (AHP) is widely preferred for solving multi-criteria decision-making problems in real situations, it is insufficient to explain uncertain conditions in especially pair-wise comparison stage. Most of human’s judgments are not represented as exact numbers. Since some of the evaluation criteria are subjective and qualitative in nature, it is very difficult for the decision-maker to express the preferences using exact numerical values and to provide exact pair-wise comparison judgments (Chan & Kumar, 2007). Fuzzy evaluations in decision making process are very useful to tackle this disadvantage of AHP. To select the best supplier for a washing machine company, this study proposes a fuzzy extended AHP (FEAHP) approach using triangular fuzzy numbers to represent decision makers’ comparison judgments and extent analysis method to decide the final priority of different decision criteria. The presented fuzzy AHP uses the linguistic variables and triangular fuzzy numbers as a pair-wise comparison scale for deriving the priorities of different selection attributes and sub-attributes. After pair-wise comparisons, the priority weights for main attributes, sub-attributes and alternatives are combined to determine the priority weights of the alternative suppliers. The supplier with the highest priority weight is selected as the best supplier. Macros in MS Excel are used to calculate the priority weights of the alternatives based on the questionnaire forms used to facilitate comparisons of main attributes, sub-attributes and alternatives. In particular, the approach presented can handle the inherent uncertainty and imprecision of the human decision making process and provide the flexibility needed for the decision maker to understand the decision problem. The remainder of the paper is organized as follows: In Section 2, researches related with supplier selection problem in literature are given. In Section 3, we explain AHP, fuzzy AHP, fuzzy numbers, fuzzy sets and extent analysis method on fuzzy AHP. In Section 4, a FEAHP based approach to select the best supplier firm providing the most satisfaction for the criteria determined is developed and the steps of each stage of the procedure is explained in detail. The paper ends with concluding remarks in Section 5.

Supplier selection is a broad comparison of suppliers using a common set of criteria and measures to identify suppliers with the highest potential for meeting a firm’s needs consistently and at an acceptable cost. Selecting the right suppliers significantly reduces the purchasing costs and improves corporate competitiveness therefore supplier selection one of the most important decision making problems. In this study, a fuzzy AHP based approach is presented to select the best supplier firm providing the most customer satisfaction for the criteria determined for a washing machine company. Three main attributes and 14 sub-attributes are determined based on literature survey and the experience of the expert in the Production Planning Department. Comparison of the main attributes and sub-attributes and suppliers are made using a questionnaire. The weights of the main attributes, sub-attributes and alternatives are calculated using fuzzy AHP approach. Best supplier is selected after computing the overall score of each supplier. To select the best supplier, all of the calculations in fuzzy AHP are written using macros in MS Excel. It has several advantages. The supplier selection problem can be solved in a shorter and more accurate way. It permits making hand-made errors while making the mathematical calculations. Also future changes in the preferences of the main attributes, sub-attributes or alternatives can be easily reflected on the priority weights of the alternatives without calculating all of the steps from the beginning once more. In this study, supplier selection process is presented for only one important part of the washing machine. Fuzzy AHP approach can be easily adopted to select best supplier for each of other important parts of the washing machine using the macros in MS Excel. This study can be extended to incorporate the supplier’s capacity constraints in the supplier selection process. Thus an integrated AHP and mathematical programming model can be proposed to determine the best suppliers and the optimal order quantities from the chosen suppliers. Also, the macros in MS Excel can be integrated into ERP software. Suppliers’ information, such as delivery time, product quality, professionalism and etc., can be collected from database of ERP. This integration may reduce time consuming efforts in supplier selection process.