Presenting a New Approach to Improve Effectiveness and Select the Most Critical Equipment Using Data Mining, Fuzzy DEMATEL, FMEA and FTA Approaches

Subject Areas : Industrial Management

Mohammad  Ehsanifar ¹ (Assistant Professor, Department of Industrial Engineering, Islamic Azad University, Arak branch, Arak, Iran)
Nima  Hamta ² (Assistant Professor, Department of Mechanical Engineering, Arak University of Technology, Arak, Iran)
Parisa  Bolhasani ³ (MSc Graduate, Department of Industrial Engineering, Islamic Azad University, Arak branch, Arak, Iran)

Received: 2017-08-30 Accepted : 2017-11-22 Published : 2017-12-24

Keywords:

Abstract :

Taking attention to reliability and maintenance management conception has substantially significantly increased over the recent decades. This paper proposes and integration of DATA MINING, Fuzzy DEMATEL, and FMEA technique in order to improve the reliability and effectiveness of maintenance management in Shazand Petrochemical Company. Firstly, the most critical cluster is selected among final clusters obtained from software by utilizing DATA MINING technique. Secondly, Fuzzy DEMATEL technique is used to identify a collection of most critical and most effective equipment of critical cluster under fuzzy condition. Finally, the FMEA and FTA techniques applied to identify the risks numbers and the main causes of the failure and then the solution will be proposed to solve the problems and improve the system.

References:

1. Alizadeh, S., and Malek Mohammadi, S. (2012). Data mining & knowledge discovery. Khajeh Nasir Toosi University of Technology Publication. Tehran.


2. Barforoush, N., Karbasian, M., Molaverdi, N. (2013). The use of CMMS and FMEA for maintenance support for reliability (RCM), Homa Journal, 40.


3. Carretero, J., et al. (2003). Applying RCM in large scale systems: A case study with railway networks", Reliability Engineering and System Safety, 82, 257-273.


4. Dekker, R., and van Rijn, C. (1996). PROMPT, a decision support system for opportunity-based preventive maintenance. In Reliability and Maintenance of Complex Systems (pp. 530-549). Springer, Berlin, Heidelberg.


5. Fontela, E., and Gabus, A. (1976). The DEMATEL observer, DEMATEL 1976 Report, Battelle Geneva Research Center, Switzerland, Geneva.


6. Haj-shirmohammadi, A. (2011). Maintenance planning, Esfahan, Ghazal Publishing Press.


7. John, B., and Bowles, R.D. (1995). Bonnell, Fuzzy Logic Priorization of Failure in a System Failure mode and effects Criticality analysis, Reliability Engineering and System Safety, 50, 203-213.


8. Berry, M.J.A. and Tanoff, G. (1997). Data Mining Technologies, New York: Jon Willey & Sons.


9. Sankar, N.R. and Prabhu, B.S. (2011). Modified approach for prioritization of failures in a system failure mode and e_ects analysis, Int J Qual Reliab Manage, 18(3), 324-35.


10. Sekhavati, A., and Norouzi, H. (2013). Application of error tree analysis in a gas pressure booster unit, Journal of Management of Oil and Gas Production Supervision.


11. Tahmasebi, F., and Shahidi, M. (2015). Data mining of identified risks using the FMEA technique in the insurance industry, First Scientific Conference on New Findings of Management Science, Entrepreneurship and Education, Tehran, Association for the Development and Promotion of Basic Sciences and Technology.


12. Worsham, W. C., & Senior Consultant, R. C. I. (2000). Is preventive maintenance necessary?. Maintenance Resources On-Line Magazine, 2225-0492.


13. Zafari, M., Nourbakhsh, Z., and SHahba, S. (2012). Evaluation and risk management in steel section production plants using FMEA and Data mining techniques, 2^nd Conference on Environmental Planning and Management, Tehran, University of Tehran.