System Engineering and Productivity

System Engineering and Productivity

Comprehensive Model for Evaluating Maintenance and Repair Policies Based on Interval fuzzy Numbers

Document Type : Research Paper

Authors
1 Corresponding author: Ph.D. Student, Department of Industrial Engineering, Faculty of Industrial Engineering and Systems , Isfahan University of Technology, Isfahan, Iran.
2 Assistant Professor, Department of Industrial Engineering, Faculty of Industrial Engineering and Systems , Isfahan University of Technology, Isfahan, Iran.
Abstract
Maintenance and repairs in organizations are becoming more and more important. With the increasing importance of equipment maintenance, various policies have been created for implementing maintenance and repairs. Organizations are looking to choose the best maintenance and repairs policy for themselves in order to reduce failure costs and optimize the costs of implementing the policy. As a result, multiple criteria are involved in choosing the optimal maintenance and repairs policy. Scoring the criteria is often not possible as a definite number, so the need to use fuzzy logic is felt. In this research, a method for evaluating maintenance and repairs policies with a fuzzy approach is presented. In the first step, the fuzzy dematel technique was used to weight the criteria. Then, the gray group analysis method based on interval fuzzy numbers was used to rank the options. Finally, a case study was conducted to better understand the method.

Copyright ©, Mohammad Ali Gorji, Mohammad Bagher Jamali

 

License

This article is released under the Creative Commons Attribution (CC BY 4.0) license. Anyone is free to copy, share, translate, and adapt this article for any purpose, whether commercial or non-commercial, as long as proper citation is given to the authors and original publication.

Aghaee, R., A. Aghaee, and R. Mohammad Hoseini Najizadeh, Key effective factors on Agile Maintenance in vehicle industry using fuzzy Delphi method and Fuzzy DEMATEL. Industrial Management Journal, 2015. 7(4): p. 641-672. khodayari, M. and S. Abdollahzadeh, Proposing an Approach to Determine the Appropriate Multi-product Preventive and Maintenance Policies Using Simulation and MCDM. Industrial Management Journal, 2018. 10(2): p. 279- 296.
Fitouhi, M.-C. and M. Nourelfath, Integrating noncyclical preventive maintenance scheduling and production planning for multi-state systems. Reliability Engineering & System Safety, 2014. 121: p. 175-186. Lam, C.T. and R. Yeh, Optimal maintenance-policies for deteriorating systems under various maintenance strategies. IEEE Transactions on reliability, 1994. 43(3): p. 423-430.
sayed hosseini, S.M, Systematic planning of maintenance and repair system in industries and services. Industrial Management Organization Publications. Third edition.1384(in persian)
Paz, N.M. and W. Leigh, Maintenance scheduling: issues, results and research needs. International Journal of Operations & Production Management, 1994. 14(8): p. 47-69.
Zhao, Z., et al., Predictive maintenance policy based on process data. Chemometrics and Intelligent Laboratory Systems, 2010. 103(2): p. 137-143.
Jardine, A.K., D. Lin, and D. Banjevic, A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical systems and signal processing, 2006. 20(7): p. 1483-1510.
Esmaeilian, G., F. Lourak zadeh, and R. Zareayan, Evaluating and comparing the implementation effectiveness of corrective maintenance and preventive maintenance with a systems dynamic approach (case study: Symcan company). Industrial Management Journal, 2015. 7(2): p. 189-214. Bevilacqua, M. and M. Braglia, The analytic hierarchy process applied to maintenance strategy selection. Reliability Engineering & System Safety, 2000. 70(1): p. 71-83.
Wang, L., J. Chu, and J. Wu, Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process. International journal of production economics, 2007. 107(1): p. 151-163.
Triantaphyllou, E., et al., Determining the most important criteria in maintenance decision making. Journal of Quality in Maintenance Engineering, 1997. 3(1): p. 16-28.
Wu, W.-W., Choosing knowledge management strategies by using a combined ANP and DEMATEL approach. Expert Systems with Applications, 2008. 35(3): p. 828-835.
Wu, W.-W. and Y.-T. Lee, Developing global managers’ competencies using the fuzzy DEMATEL method. Expert systems with applications, 2007. 32(2): p. 499-507.
Chang, B., C.-W. Chang, and C.-H. Wu, Fuzzy DEMATEL method for developing supplier selection criteria. Expert systems with Applications, 2011. 38(3): p. 1850-1858.
Tseng, M.-L., A causal and effect decision making model of service quality expectation using grey-fuzzy DEMATEL approach. Expert systems with applications, 2009. 36(4): p. 7738-7748.
Tseng, M.-L. and Y.H. Lin, Application of fuzzy DEMATEL to develop a cause and effect model of municipal solid waste management in Metro Manila. Environmental monitoring and assessment, 2009. 158(1-4): p. 519.
Wang, Z., et al., Waste-to-energy, municipal solid waste treatment, and best available technology: comprehensive evaluation by an interval-valued fuzzy multi-criteria decision making method. Journal of Cleaner Production, 2018. 172: p. 887-899.
Vujanović, D., et al., Evaluation of vehicle fleet maintenance management indicators by application of DEMATEL and ANP. Expert Systems with Applications, 2012. 39(12): p. 10552-10563.
AGHAEE, R., A. AGHAEE, and H.N.R. MOHAMMAD, Key effective factors on Agile Maintenance in vehicle industry using fuzzy Delphi method and Fuzzy DEMATEL. 2016.
Volume 2, Issue 1 - Serial Number 2
Serial No. 2, Spring Quarterly
Spring 2022
Pages 51-74

  • Receive Date 04 May 2022
  • Revise Date 15 June 2022
  • Accept Date 18 June 2022
  • First Publish Date 18 June 2022
  • Publish Date 22 May 2022