Fuzzy MCDM procedure for evaluating flexible manufacturing system alternatives


Karsak E.

Conference on Leading Technology Change - Management Issues and Challenges, New-Mexico, Amerika Birleşik Devletleri, 13 - 15 Ağustos 2000, ss.93-98 identifier identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/ems.2000.872483
  • Basıldığı Şehir: New-Mexico
  • Basıldığı Ülke: Amerika Birleşik Devletleri
  • Sayfa Sayıları: ss.93-98
  • Galatasaray Üniversitesi Adresli: Evet

Özet

Considering the high required capital outlay and moderate risk of a flexible manufacturing system (FMS) investment, economic justification techniques are insufficient by themselves since they cannot cope with the benefits such as flexibility and enhanced quality offered by advanced manufacturing technologies. A robust decision making procedure for selection of flexible manufacturing systems requires the consideration of both economic and strategic investment measures. In this paper, a fuzzy multicriteria decision making (MCDM) framework based on the concepts of ideal and negative-ideal solutions is presented for the selection of an FMS from a set of mutually exclusive alternatives. The proposed method provides the means for incorporating the economic figure of merit as well as the strategic performance variables. Initially, the selection criteria and their importance weights are determined. Linguistic variables are used to indicate the importance weight of each criterion. Then, the decision matrix containing the criteria values for the FMS alternatives is normalized to obtain unit-free elements. Afterwards, the weighted normalized decision matrix is obtained by taking the importance weight of each criterion into consideration. The ideal solution and the negative-ideal solution are determined by ranking the weighted normalized values for each criterion. Next, the distance between each FMS alternative, and the ideal and negative-ideal solutions are computed. Finally, the ranking order of the FMS alternatives is obtained based on their relative proximity to the ideal solution.