Fuzzy TOPSIS-based computerized maintenance management system selection


Uysal F., TOSUN Ö.

Journal of Manufacturing Technology Management, cilt.23, sa.2, ss.212-228, 2012 (Scopus) identifier

  • Yayın Türü: Makale / Derleme
  • Cilt numarası: 23 Sayı: 2
  • Basım Tarihi: 2012
  • Doi Numarası: 10.1108/17410381211202205
  • Dergi Adı: Journal of Manufacturing Technology Management
  • Derginin Tarandığı İndeksler: Scopus
  • Sayfa Sayıları: ss.212-228
  • Anahtar Kelimeler: Computer software, Computerized maintenance management system, Fuzzy TOPSIS, Maintenance programmes, Manufacturing technology management
  • Akdeniz Üniversitesi Adresli: Evet

Özet

Purpose The purpose of this paper is to provide a structured methodology to permit the optimal selection of the best-suited computerized maintenance management system (CMMS) software within maintenance information technologies. Design/methodology/approach The analysis has been executed adopting a multi-attribute decision-making methodology, namely the technique for order preference by similarity to an ideal solution (TOPSIS). For the selection process, 17 criteria under five main heading have been defined. Data obtained from questionnaires and interviews with the company's maintenance managers have been used in fuzzy TOPSIS. Findings The application of the proposed approach allows the maintenance practitioners to concentrate on a limited subset of CMMS applications and to compare their actual capabilities in order to select the right one, rather than considering only their purchase cost. Research limitations/implications Comparisons with other multi-attribute decision-making techniques such as AHP (analytic hierarchy process) and ELECTRE (elimination and choice expressing reality) under fuzzy conditions can be done for further research. Practical implications This paper is a very useful source of information both for maintenance managers and stakeholders in making decisions about the selection of CMMS software. Originality/value This paper addresses CMMS software evaluation and selection criteria for practitioners and proposes a new multi-attribute decision-making methodology, hierarchical fuzzy TOPSIS, for the problem. Copyright © 2012 Emerald Group Publishing Limited. All rights reserved.