Comprehensive fuzzy FMEA model: a case study of ERP implementation risks


OPERATIONAL RESEARCH, vol.20, no.2, pp.795-826, 2020 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 20 Issue: 2
  • Publication Date: 2020
  • Doi Number: 10.1007/s12351-017-0338-1
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, IBZ Online, ABI/INFORM, Aerospace Database, zbMATH, Civil Engineering Abstracts
  • Page Numbers: pp.795-826
  • Keywords: Fuzzy FMEA, Fuzzy preference programming, Fuzzy cognitive maps, Fuzzy graph-theoretical matrix approach, Enterprise resource planning, Risk management, SYSTEM FAILURE MODE, DECISION-MAKING, DEFUZZIFICATION, PRIORITIZATION, DIGRAPH, TOPSIS
  • Dokuz Eylül University Affiliated: Yes


Failure mode and effects analysis (FMEA) is a prominent engineering technique for eliminating the potential failures emerged from various systems such as products, processes, designs, or systems. In the traditional FMEA, for each risk factor, severity, occurrence, and detectability ratings are multiplied and risk ranking number (RPN) is calculated. However, traditional FMEA has been subject of severe criticism in the literature and significant efforts have been made to overcome the shortcomings of the RPN. The present paper aims to put a step forward to enhance fuzzy FMEA by proposing a hybrid multi-attribute decision making model by combining fuzzy preference programming, fuzzy cognitive maps, and fuzzy graph-theoretical matrix approach. Fuzzy preference programming method is used to derive ratings of risk factors from incomplete, imprecise, and reciprocal pairwise comparison judgments. The causal dependencies among failure modes are modelled via fuzzy cognitive maps in order to capture the long term influences. Finally, fuzzy graph-theoretical matrix approach is employed to calculate risk priority indices of failure modes by taking into account interactions among risk factors. Although the FMEA method has been implemented in variety of technical problems, its potential in analyzing complex information systems have not been fully explored. Therefore, the proposed model is implemented in evaluating enterprise resource planning implementation risks in a real life case study.