Decision model for advanced manufacturing technology selection using fuzzy regression and fuzzy optimization

ŞENER Z., KARSAK E. E.

IEEE International Conference on Systems, Man and Cybernetics, Montreal, Canada, 7 - 10 October 2007, pp.2400-2404 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icsmc.2007.4413979
  • City: Montreal
  • Country: Canada
  • Page Numbers: pp.2400-2404
  • Galatasaray University Affiliated: Yes

Abstract

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.