A new FMEA method by integrating fuzzy belief structure and TOPSIS to improve risk evaluation process

Failure mode and effect analysis (FMEA) model is a technique used to evaluate the risk. This paper aimed to propose a new FMEA model combining technique for order of preference by similarity to ideal solution (TOPSIS) and belief structure to overcome the shortcomings of the traditional index of FMEA. In this paper, the fuzzy belief TOPSIS method is combined with FMEA to introduce a belief structure FMEA to describe the expert knowledge by a number of linguists as a grammatical phenomenon. Moreover, the weights of components in FMEA index can be different from each other. Therefore, the flexibility of assigning weight to each factor in this method is more compatible to the real decision-making situation. In other word, TOPSIS method is applied to determine the preference of alternatives versus risk criteria. Using linguistic terms in the fuzzy belief approach, the risk factors described a more meaningful value and decision-makers’ judgment is assigned with belief degrees through evaluation of factors. Finally, a numerical case study about the preference of cause failures of steel production process is provided to illustrate the process of proposed method, and then result and discussion is performed for each case.

[1]  Keith Case,et al.  FAILURE MODES AND EFFECTS ANALYSIS THROUGH KNOWLEDGE MODELLING , 2004 .

[2]  Donald D. Tippett,et al.  Project Risk Management Using the Project Risk FMEA , 2004 .

[3]  Moharam Habibnejad Korayem,et al.  Improvement of 3P and 6R mechanical robots reliability and quality applying FMEA and QFD approaches , 2008 .

[4]  Jiang Jiang,et al.  TOPSIS with fuzzy belief structure for group belief multiple criteria decision making , 2011, Expert Syst. Appl..

[5]  J. B. Bowles,et al.  Fuzzy logic prioritization of failures in a system failure mode, effects and criticality analysis , 1995 .

[6]  Joseph M. Derosier,et al.  Using health care Failure Mode and Effect Analysis: the VA National Center for Patient Safety's prospective risk analysis system. , 2002, The Joint Commission journal on quality improvement.

[7]  Chee Peng Lim,et al.  Fuzzy FMEA with a guided rules reduction system for prioritization of failures , 2006 .

[8]  Jin Wang,et al.  Modified failure mode and effects analysis using approximate reasoning , 2003, Reliab. Eng. Syst. Saf..

[9]  Mesut Kumru,et al.  Fuzzy FMEA application to improve purchasing process in a public hospital , 2013, Appl. Soft Comput..

[10]  David L. Olson,et al.  Comparison of weights in TOPSIS models , 2004, Math. Comput. Model..

[11]  Jian-Bo Yang,et al.  Risk evaluation in failure mode and effects analysis using fuzzy weighted geometric mean , 2009, Expert Syst. Appl..

[12]  Celso Marcelo Franklin Lapa,et al.  Fuzzy FMEA applied to PWR chemical and volume control system , 2004 .

[13]  Mahdi Bahrami,et al.  Innovation and Improvements In Project Implementation and Management; Using FMEA Technique , 2012 .

[14]  Ahmet Can Kutlu,et al.  Fuzzy failure modes and effects analysis by using fuzzy TOPSIS-based fuzzy AHP , 2012, Expert Syst. Appl..

[15]  Liang-Hsuan Chen,et al.  Fuzzy linear programming models for new product design using QFD with FMEA , 2009 .

[16]  J. P. Modak,et al.  Application of RCM to a medium scale industry , 2002, Reliab. Eng. Syst. Saf..

[17]  Marcello Braglia,et al.  Fuzzy TOPSIS approach for failure mode, effects and criticality analysis , 2003 .

[18]  Celso Marcelo Franklin Lapa,et al.  Fuzzy inference to risk assessment on nuclear engineering systems , 2007, Appl. Soft Comput..

[19]  Ching-Hsue Cheng,et al.  A risk assessment methodology using intuitionistic fuzzy set in FMEA , 2010, Int. J. Syst. Sci..

[20]  Loon Ching Tang,et al.  Fuzzy assessment of FMEA for engine systems , 2002, Reliab. Eng. Syst. Saf..

[21]  Wei Wu,et al.  Development of a risk-based maintenance strategy using FMEA for a continuous catalytic reforming plant , 2012 .

[22]  Yung-Chia Chang,et al.  Enhancing FMEA assessment by integrating grey relational analysis and the decision making trial and evaluation laboratory approach , 2013 .

[23]  Pema Wangchen Bhutia,et al.  Appication of ahp and topsis method for supplier selection problem , 2012 .

[24]  B. Fuchs,et al.  Failure mode and effects analysis application to critical care medicine. , 2005, Critical care clinics.

[25]  Jin Wang,et al.  Decision support framework for risk management on sea ports and terminals using fuzzy set theory and evidential reasoning approach , 2012, Expert Syst. Appl..