A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes

• We construct a hierarchical model for fuzzy multi-attribute decision making.
• Expert judgments are handled using fuzzy numbers in the fuzzy ANP and grey numbers in COPRAS-G.
• We present an integrated hierarchy of solutions based on the fuzzy ANP and COPRAS-G to evaluate the machine tools.
• We compare the results of fuzzy ANP and COPRAS-G with other methods (TOPSIS-G, SAW-G, GRA).
• We conduct a case study in machine tool selection at the University Lab of Manufacturing.

Global economic competition has spurred the manufacturing sector to improve and invest in modern equipment to satisfy the needs of the market. In particular, machine tool selection is the most important problem; it plays a primary role in the improvement of productivity and flexibility in the manufacturing environment and involves the imprecise, vague and uncertain information. This paper presents the hybrid approach of the fuzzy ANP (Analytic Network Process) and COPRAS-G (COmplex PRoportional ASsessment of alternatives with Grey relations) for fuzzy multi-attribute decision-making in evaluating machine tools with consideration of the interactions of the attributes. The fuzzy ANP is used to handle the imprecise, vague and uncertain information from expert judgments and model the interaction, feedback relationships and interdependence among the attributes to determine the weights of the attributes. COPRAS-G is employed to present the preference ratio of the alternatives in interval values with respect to each attribute and calculate the weighted priorities of the machine alternatives. Alternatives are ranked in ascending order by priority. As a demonstration of the proposed model, a numerical example is implemented based on the collected data and the literature. The result is then compared with the rankings provided by other methods such as TOPSIS-G, SAW-G and GRA. Moreover, a sensitivity analysis is conducted to verify the robustness of the ranking. The result highlights that the hybrid approach of the fuzzy ANP and COPRAS-G is a highly flexible tool and reaches an effective decision in machine tool selection.