A decision model for advanced manufacturing technology selection using fuzzy regression and fuzzy optimization

Advanced manufacturing technologies provide a great potential for improving manufacturing performance to compete in the global markets. In this paper, we present a decision model based on fuzzy linear regression with non-symmetric triangular fuzzy coefficients and fuzzy optimization for technology selection. Fuzzy regression is introduced in the model to assess the vagueness of functional relationships among decision variables. Non-symmetric triangular fuzzy coefficients are employed to account for imprecision and vagueness that cannot be modeled properly using symmetric fuzzy coefficients. The proposed decision methodology is illustrated through a flexible manufacturing system selection problem, and the results of the sensitivity analysis are presented.