In this paper, emphasizing the real conditions prevailing in production industries, a new optimization model is developed in order to optimally schedule preventive maintenance and repair activities in a multi-component maintainable manufacturing systemaddressing a novel approach. It is assumed that failures or inspections are not only causes of stopping devices but also some other activities (non-failure stops) may interrupt the production process. The presented mathematical model utilizes these interruptions as opportunities to perform some maintenance activities. Failure interaction between components is also considered and the rate of failure of each component due to shocks from other components may be increased by a certain percentage. In addition to preventive maintenance and repairs, in the case of sudden failure of any component, corrective maintenance is implemented. Besides, the cost of stopping the system for performing maintenance activities is considered dependent on the duration of maintenance execution. Due to the complexity of the structure of the proposed model, the Genetic algorithm is adapted as the solution approach and its parameters are adjusted by the Taguchi method. A numerical example is solved and analyzed.Finally, a comparison between the exact method and the developed algorithm is provided to examine its efficiency and the impacts of the rise in problem sizes on the performance of the algorithm.
[1] Venkataraman, V. (2007). Maintenance engineering and management. New Delhi: PHI Learning Pvt. Ltd.
[2] Mo, H., Sansavini, G. and Xie, M. \Performance-based maintenance of gas turbines for reliable control of degraded power systems", Mech Syst Signal Process, 103, pp. 398-412 (2019).
[3] Barlow, R., & Hunter, L. (1960). Optimum preventive maintenance policies. Operations Research, 8, 90–100.
[4] Cha, J. H., Finkelstein, M., & Levitin, G. (2018). Bivariate preventive maintenance of systems with lifetimes dependent on a random shock process. European Journal of Operational Research, 266, 122–134.
[5] Fouladirad, M., Paroissin, C., & Grall, A. (2018). Sensitivity of optimal replacement policies to lifetime parameter estimates. European Journal of Operational Research, 266, 963–975.
[6] Hu, J., Zhang, L., & Liang, W. (2012). Opportunistic predictive maintenance for complex multi-component systems based on DBN-HAZOP model. Process Safety and Environmental Protection, 90(5), 376-388.
[7] Hadian, S. M., Farughi, H., & Rasay, H. (2021). Joint planning of maintenance, buffer stock and quality control for unreliable, imperfect manufacturing systems. Computers & Industrial Engineering, 157, 107304.
[8] Hadian, S. M., Farughi, H., & Rasay, H. (2021). A mathematical model for the joint planning of maintenance and safety stock in deteriorating imperfect manufacturing systems. Scientia Iranica.
[9] Rahimi Komijani, H., Shahin, M., & Jabbarzadeh, A. (2018). Optimal policy of condition-based maintenance considering probabilistic logistic times and the environmental contamination issues. International Journal of Engineering, 31(2), 357-364.
[10] Taji, J., Farughi, H., & Rasay, H. An integrated Markov chain model for the economic-statistical design of adaptive multivariate control charts and maintenance planning. European J. of Industrial Engineering. In press. DOI: 10.1504/EJIE.2023.10044732.
[11] Rasay, , Naderkhani, F., & Azizi, F. (2022). Opportunistic maintenance integrated model for a two-stage manufacturing process. The International Journal of Advanced Manufacturing Technology, 119(11), 8173-8191.
[12] Malik, M. A. K. (1979). Reliable preventive maintenance scheduling. AIIE transactions, 11(3), 221-228.
[13] Nakagawa, T. (1988). Sequential imperfect preventive maintenance policies. Reliability, IEEE Transactions on, 37(3), 295-298.
[14] Lin, D., Zuo, M.J, Yam, R.C.M. (2001). Sequential imperfect preventive maintenance models with two categories of failure modes. Naval Research Logistics, 48(2), 172-183.
[15] Liu, B., Yeh, R. H., Xie, M., & Kuo, W. (2017c). Maintenance scheduling for multicomponent systems with hidden failures. IEEE Transactions on Reliability, 66, 1280–1292.
[16] Zhang, N., & Yang, Q. (2015). Optimal maintenance planning for repairable multi-component systems subject to dependent competing risks. IIE Transactions, 47, 521–532.
[17] Sasieni, M. (1956). A Markov Chain Process in Industrial Replacement. Operational Research Quarterly, 7, 148–155.
[18] Wu, S., Chen, Y., Wu, Q., & Wang, Z. (2016). Linking component importance to optimisation of preventive maintenance policy. Reliability Engineering and System Safety, 146, 26–32.
[19] Canh Vu, H., Do, P., & Barros, A. (2016). A stationary grouping maintenance strategy using mean residual life and the birnbaum importance measure for complex structures. IEEE Transactions on Reliability, 65, 217–234.
[20] Hajipour, Y., & Taghipour, S. (2016). Non-periodic inspection optimization of multi-component and k-out-of-m systems. Reliability Engineering and System Safety, 156, 228–243.
[21] Barros, A., Berenguer, C., Grall, A. (2006). A Maintenance Policy for Two-Unit Parallel Systems Based on Imperfect Monitoring Information. Reliability Engineering and System Safety, 91, 131–136.
[22] Xu, M., Jin, X., Kamarthi, S., & Noor-E-Alam, M. (2018). A failure-dependency modeling and state discretization approach for condition-based maintenance optimization of multi-component systems. Journal of manufacturing systems, 47, 141-152.
[23] Tsai, H.-N., Sheu, S.-H., & Zhang, Z. G. (2017). A trivariate optimal replacement policy for a deteriorating system based on cumulative damage and inspections. Reliability Engineering and System Safety, 160, 74–88.
[24] Sheu, S.-H., Liu, T.-H., Zhang, Z. G., & Ke, J.-C. (2015c). Extended preventive replacement policy for a two-unit system subject to damage shocks. International Journal of Production Research, 53, 4614–4628.
[25] Zhang, N., Fouladirad, M., & Barros, A. (2018). Optimal imperfect maintenance cost analysis of a two-component system with failure interactions. Reliability Engineering and System Safety, 177, 24–34.
[26] Moghaddam, K. S., & Usher, J. S. (2011). A new multi-objective optimization model for preventive maintenance and replacement scheduling of multi-component systems. Engineering Optimization, 43(7), 701-719.
[27] Moghaddam, K. S. (2013). Multi-objective preventive maintenance and replacement scheduling in a manufacturing system using goal programming. International Journal of Production Economics, 146(2), 704-716.
Taji, J., Farughi, H., & Rasay, H. (2022). A New Approach to Preventive Maintenance Planning Considering Non-Failure Stops and Failure Interdependence Between Components. Advances in Industrial Engineering, 56(2), 231-249. doi: 10.22059/aie.2022.344909.1843
MLA
Jalal Taji; Hiwa Farughi; Hasan Rasay. "A New Approach to Preventive Maintenance Planning Considering Non-Failure Stops and Failure Interdependence Between Components", Advances in Industrial Engineering, 56, 2, 2022, 231-249. doi: 10.22059/aie.2022.344909.1843
HARVARD
Taji, J., Farughi, H., Rasay, H. (2022). 'A New Approach to Preventive Maintenance Planning Considering Non-Failure Stops and Failure Interdependence Between Components', Advances in Industrial Engineering, 56(2), pp. 231-249. doi: 10.22059/aie.2022.344909.1843
VANCOUVER
Taji, J., Farughi, H., Rasay, H. A New Approach to Preventive Maintenance Planning Considering Non-Failure Stops and Failure Interdependence Between Components. Advances in Industrial Engineering, 2022; 56(2): 231-249. doi: 10.22059/aie.2022.344909.1843
)