Sustainable reliability centered maintenance optimization considering risk attitude

Document Type: Research Paper

Authors

1 Department of Industrial Engineering, Islamic Azad University, Najafabad Branch, Iran.

2 Department of Industrial Engineering, Islamic Azad University, Lenjan Branch, Isfahan, Iran.

Abstract

Maintenance costs are one of the major costs in plants and companies. The observation in many cases illustrates the lack of plans or mistakes in maintenance activities that incurred great costs. In this study, the number of equipment failures have been determined. Then the failure rate and reliability of each equipment are calculated. The third step calculates total system reliability so the initial plan is presented. After that, by using the obtained information, the sustainability aspects of the program will generate and the maintenance costs and sustainability functions will assess. At the end, this multi-objective optimization problem is solved by MOPSO algorithm and the results are compared with a simulation method. As a result, with this reliability centered maintenance program, the reliability of each equipment, as well as the whole system are improved; economic aspect of sustainability and customer satisfaction are increased; environmental pollutions and maintenance costs are decreased by offering more reliability based program; a scheduling plan for each maintenance procedures is provided and also more stable internet connection is established by reducing the system failures.

Keywords

References

[1]      Ben-Daya, M., Kumar, U., & Murthy, D. P. (2016). Introduction to maintenance engineering: modelling, optimization and management. John Wiley & Sons.

[2]     Vishnu, C. R., & Regikumar, V. (2016). Reliability based maintenance strategy selection in process plants: a case study. Procedia technology, 25, 1080-1087.

[3]     Alsyouf, I. (2007). The role of maintenance in improving companies’ productivity and profitability. International journal of production economics, 105(1), 70-78.

[4]     Ahuja, I. P. S., & Khamba, J. S. (2008). Total productive maintenance: literature review and directions. International journal of quality & reliability management, 25(7), 709-756.

[5]     Muller, A., Suhner, M. C., & Iung, B. (2008). Formalisation of a new prognosis model for supporting proactive maintenance implementation on industrial system. Reliability engineering & system safety, 93(2), 234-253.

[6]     Van Horenbeek, A., & Pintelon, L. (2013). A dynamic predictive maintenance policy for complex multi-component systems. Reliability engineering & system safety, 120, 39-50.

[7]     Arunraj, N. S., & Maiti, J. (2010). Risk-based maintenance policy selection using AHP and goal programming. Safety science, 48(2), 238-247.

[8]     Dybå, T., & Dingsøyr, T. (2008). Empirical studies of agile software development: A systematic review. Information and software technology, 50(9-10), 833-859.

[9]     Cassady, C. R., Pohl, E. A., & Paul Murdock, W. (2001). Selective maintenance modeling for industrial systems. Journal of quality in maintenance engineering, 7(2), 104-117.

[10] Van Houten, F. J., & Kimura, F. (2000). The virtual maintenance system: a computer-based support tool for robust design, product monitoring, fault diagnosis and maintenance planning. CIRP annals-manufacturing technology, 49(1), 91-94.

[11] Zio, E. (2009). Reliability engineering: Old problems and new challenges. Reliability engineering & system safety, 94(2), 125-141.

[12] Bichon, B. J., McFarland, J. M., & Mahadevan, S. (2011). Efficient surrogate models for reliability analysis of systems with multiple failure modes. Reliability engineering & system safety, 96(10), 1386-1395.

[13] Lisnianski, A., Elmakias, D., Laredo, D., & Haim, H. B. (2012). A multi-state Markov model for a short-term reliability analysis of a power generating unit. Reliability engineering & system safety, 98(1), 1-6.

[14] Barabady, J., & Kumar, U. (2008). Reliability analysis of mining equipment: A case study of a crushing plant at Jajarm Bauxite Mine in Iran. Reliability engineering & system safety, 93(4), 647-653.

[15] Nowlan, F. S., & Heap, H. F. (1978). Reliability-centered maintenance. United Air Lines Inc San Francisco Ca.

[16] Rausand, M. (1998). Reliability centered maintenance. Reliability engineering & system safety, 60(2), 121-132

[17] Niu, G., Yang, B. S., & Pecht, M. (2010). Development of an optimized condition-based maintenance system by data fusion and reliability-centered maintenance. Reliability engineering & system safety, 95(7), 786-796.

[18] Zhou, X., Xi, L., & Lee, J. (2007). Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation. Reliability engineering & system safety, 92(4), 530-534.

[19] Li, D., & Gao, J. (2010). Study and application of Reliability-centered Maintenance considering Radical Maintenance. Journal of loss prevention in the process industries, 23(5), 622-629.

[20] Samrout, M., Châtelet, E., Kouta, R., & Chebbo, N. (2009). Optimization of maintenance policy using the proportional hazard model. Reliability engineering & system safety, 94(1), 44-52.

[21] Selvik, J. T., & Aven, T. (2011). A framework for reliability and risk centered maintenance. Reliability engineering & system safety, 96(2), 324-331.

[22] Ba, K., Dellagi, S., Rezg, N., & Erray, W. (2016). Joint optimization of preventive maintenance and spare parts inventory for an optimal production plan with consideration of CO2 emission. Reliability engineering & system safety, 149, 172-186.

[23] Khatab, A., & Aghezzaf, E. H. (2016). Selective maintenance optimization when quality of imperfect maintenance actions are stochastic. Reliability engineering & system safety, 150, 182-189.

[24] Apeland, S., & Aven, T. (2000). Risk based maintenance optimization: foundational issues. Reliability engineering & system safety, 67(3), 285-292.

[25] Keivanpour, S., & Kadi, D. A. (2015). A sustainable approach to Aircraft Engine Maintenance. IFAC-PapersOnLine, 48(3), 977-982.

[26] Saniuk, A., Jasiulewicz-Kaczmarek, M., Samolejová, A., Saniuk, S., & Lenort, R. (2015). Environmental favourable foundries through maintenance activities. Metalurgija, 54(4), 725-728.

[27] Sabatino, S., Frangopol, D. M., & Dong, Y. (2015). Sustainability-informed maintenance optimization of highway bridges considering multi-attribute utility and risk attitude. Engineering structures, 102, 310-321.

[28] Ait-Kadi, D., Duffuaa, S. O., Knezevic, J., & Raouf, A. (2009). Handbook of maintenance management and engineering (Vol. 7). London: Springer.

[29] Stein, S. M., Young, G. K., Trent, R. E., & Pearson, D. R. (1999). Prioritizing scour vulnerable bridges using risk. Journal of infrastructure systems, 5(3), 95-101.

[30] Zhu, B., & Frangopol, D. M. (2012). Risk-based approach for optimum maintenance of bridges under traffic and earthquake loads. Journal of structural engineering, 139(3), 422-434.

[31] Smith, D. (2011). Reliability, maintainability and risk: Practical safety-related systems engineering methods. Butterworth-Heinemann

[32] Rackwitz, R. (2002). Optimization and risk acceptability based on the life quality index. Structural safety, 24(2-4), 297-331.

[33] Heo, J. H., Kim, M. K., & Lyu, J. K. (2014). Implementation of reliability-centered maintenance for transmission components using particle swarm optimization. International journal of electrical power & energy systems, 55, 238-245.

[34] Luke, S. (2009). Essentials of metaheuristics (Vol. 113). Raleigh: Lulu.

[35]  Lalwani, S., Singhal, S., Kumar, R., & Gupta, N. (2013). A comprehensive survey: Applications of multi-objective particle swarm optimization (MOPSO) algorithm. Transactions on combinatorics, 2(1), 39-101.

Journal of Applied Research on Industrial Engineering

Volume 5, Issue 3
Autumn 2018
Pages 205-222

Files

History

  • Receive Date: 06 July 2018
  • Revise Date: 16 August 2018
  • Accept Date: 11 November 2018

Share

How to cite

Statistics