Share:


Proposed procedure for optimal maintenance scheduling under emergent failures

    Abbas Al-Refaie Affiliation
    ; Heba Al-Shalaldeh Affiliation
    ; Natalija Lepkova   Affiliation

Abstract

Production lines are usually subjected to emergent machine failures. Such emergent failures disrupt pre-established maintenance schedules, which challenge maintenance engineers to react to those failures in real time. This research proposes an optimization procedure for optimizing scheduling repairs of emergent failures. Three optimization models are developed. Model I schedules failures in newly idle repair shops with the objective of maximizing the number of scheduled repairs. Model II maximizes the number of assigned repairs to untapped ranges. Model III maximizes both the number of assigned failure repairs and satisfaction on regular and emergency repairs by resequencing regular and emergent failures in the shop that contains the largest free margin. A real case study is provided to illustrate the proposed optimization procedure. Results reveal that the proposed models efficiently scheduled and sequenced emergent failures in the idle maintenance shops, the untapped ranges between repairs of regular failures, and in the maintenance shop with the largest free margin. In conclusions, the proposed models can greatly support maintenance engineers in planning repairs under unexpected failures. 

Keyword : emergency events, maintenance scheduling, satisfaction model, fuzzy goal programming

How to Cite
Al-Refaie, A., Al-Shalaldeh, H., & Lepkova, N. (2020). Proposed procedure for optimal maintenance scheduling under emergent failures. Journal of Civil Engineering and Management, 26(4), 396-409. https://doi.org/10.3846/jcem.2020.12315
Published in Issue
Apr 21, 2020
Abstract Views
752
PDF Downloads
251
Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

Abed, F., Chen L., Disser, Y., Groß, M., Megow, N., Meißner, J., Richter, A.T., & Rischke, R. (2019). Scheduling maintenance jobs in networks. Theoretical Computer Science, 754, 107–121. https://doi.org/10.1016/j.tcs.2018.02.020

Alayo, H., & Paucar, E. (2018). A MILP model for maintenance scheduling in transmission systems and an example application to the peruvian system. IEEE Latin America Transactions, 16(4), 1099–1104. https://doi.org/10.1109/TLA.2018.8362143

Ben-Daya, M., Ait-Kadi, D., Duffuaa, S. O., Knezevic, J., & Raouf, A. (2009). Handbook of maintenance management and engineering. Springer. https://doi.org/10.1007/978-1-84882-472-0

Bertolini, M., Mezzogori, D., & Zammori, F. (2019). Comparison of new metaheuristics, for the solution of an integrated jobs-maintenance scheduling problem. Expert Systems with Applications, 122, 118–136. https://doi.org/10.1016/j.eswa.2018.12.034

Cassady, C. R., & Kutanoglu, E. (2003). Minimizing job tardiness using integrated preventive maintenance planning and production scheduling. IIE Transactions, 35(6), 503–513. https://doi.org/10.1080/07408170304416

Cassady, C. R., & Kutanoglu, E. (2005). Integrating preventive maintenance planning and production scheduling for a single machine. IEEE Transactions on Reliability, 54(2), 304–309. https://doi.org/10.1109/TR.2005.845967

Chansombat, S., Pongcharoen, P., & Hicks, C. (2019). A mixedinteger linear programming model for integrated production and preventive maintenance scheduling in the capital goods industry. International Journal of Production Research, 57(1), 61–82. https://doi.org/10.1080/00207543.2018.1459923

Duenas, A., & Petrovic, D. (2008). Multi-objective genetic algorithm for single machine scheduling problem under fuzziness. Fuzzy Optimization and Decision Making, 7, 87–104. https://doi.org/10.1007/s10700-007-9026-6

El-Sharkh, M. Y., & El-Keib, A. A. (2003). Maintenance scheduling of generation and transmission systems using fuzzy evolutionary programming. IEEE Transactions on Power Systems, 18(2), 862–866. https://doi.org/10.1109/TPWRS.2003.811004

Gholami, P., & Hafezalkotob, A. (2018). Maintenance scheduling using data mining techniques and time series models. International Journal of Management Science and Engineering Management, 13(2), 100–107. https://doi.org/10.1080/17509653.2017.1314201

Grigoriu, L., & Briskorn, D. (2017). Scheduling jobs and maintenance activities subject to job-dependent machine deteriorations. Journal of Scheduling, 20(2), 183–197. https://doi.org/10.1007/s10951-016-0502-0

Hedjazi, D., Layachi, F., & Boubiche, D. E. (2019). A multi-agent system for distributed maintenance scheduling. Computers and Electrical Engineering, 77, 1–11. https://doi.org/10.1016/j.compeleceng.2019.04.016

Irawan, C. A., Ouelhadj, D., Jones, D., Stålhane, M., & Sperstad, I. B. (2017). Optimisation of maintenance routing and scheduling for offshore wind farms. European Journal of Operational Research, 256(1), 76–89. https://doi.org/10.1016/j.ejor.2016.05.059

Jian, L., & Tianyuan, T. (2015). LS-SVM based substation circuit breakers maintenance scheduling optimization. International Journal of Electrical Power & Energy Systems, 64, 1251–1258. https://doi.org/10.1016/j.ijepes.2014.09.013

Kalinowski, K., & Zemczak, M. (2015). Preparatory stages of the production scheduling of complex and multivariant products structures. In Á. Herrero, J. Sedano, B. Baruque, H. Quintián, & E. Corchado (Eds.), 10th International Conference on Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing. Springer. https://doi.org/10.1007/978-3-319-19719-7_41

Kiefer, A., Schilde, M., & Doerner, K. F. (2018). Scheduling of maintenance work of a large-scale tramway network. European Journal of Operational Research, 270(3), 1158–1170. https://doi.org/10.1016/j.ejor.2018.04.027

Liao, W., Zhang, X., & Jiang, M. (2017). Multi-objective group scheduling optimization integrated with preventive maintenance. Engineering Optimization, 49(11), 1890–1904. https://doi.org/10.1080/0305215X.2017.1280258

Liu, Q., Dong, M., & Chen, F. F. (2018). Single-machine-based joint optimization of predictive maintenance planning and production scheduling. Robotics and Computer-Integrated Manufacturing, 51, 238–247. https://doi.org/10.1016/j.rcim.2018.01.002

Lu, B., & Zhou, X. (2017). Opportunistic preventive maintenance scheduling for serial-parallel multistage manufacturing systems with multiple streams of deterioration. Reliability Engineering & System Safety, 168, 116–127. https://doi.org/10.1016/j.ress.2017.05.017

Lu, Z., Cui, W., & Han, X. (2014). Integrated production and preventive maintenance scheduling for a single machine with failure uncertainty. Computers & Industrial Engineering, 80, 236–244. https://doi.org/10.1016/j.cie.2014.12.017

Murthy, D. N. P., Atrens, A., & Eccleston, J. A. (2002), Strategic maintenance management. Journal of Quality in Maintenance Engineering, 8(4), 287–305. https://doi.org/10.1108/13552510210448504

Miyata, H. H., & Nagano, M. S. (2019). The blocking flow shop scheduling problem: A comprehensive and conceptual review. Expert Systems with Applications, 137, 130–156. https://doi.org/10.1016/j.eswa.2019.06.069

Miyata, H. H., Nagano, M. S., & Gupta, J. N. D. (2019a). Incorporating preventive maintenance into the m-machine no-wait flow-shop scheduling problem with total flow-time minimization: A computational study. Engineering Optimization, 51(4), 680–698. https://doi.org/10.1080/0305215X.2018.1485903

Miyata, H. H., Nagano, M. S., & Gupta, J. N. D. (2019b). Integrating preventive maintenance activities to the no-wait flow shop scheduling problem with dependent-sequence setup times and makespan minimization. Computers & Industrial Engineering, 135, 79–104. https://doi.org/10.1016/j.cie.2019.05.034

Nourelfath, M., Fitouhi, M. C., & Machani, M. (2010). An Integrated model for production and preventive maintenance planning in multi-state systems. IEEE Transactions on Reliability, 59(3), 496–506. https://doi.org/10.1109/TR.2010.2056412

Paprocka, I. (2019). The model of maintenance planning and production scheduling for maximising robustness. International Journal of Production Research, 57(14), 4480–4501. https://doi.org/10.1080/00207543.2018.1492752

Rasiulis, R., Ustinovichius, L., Vilutienė, T., & Popov, V. (2016). Decision model for selection of modernization measures: public building case. Journal of Civil Engineering and Management, 22(1), 124–133. https://doi.org/10.3846/13923730.2015.1117018

Rossit, D. A., Vásquez, O. C., Tohmé, F., Frutos, M., & Safe, M. D. (2019). A combinatorial analysis of the permutation and non-permutation flow shop scheduling problems. European Journal of Operational Research (In Press, Corrected Proof). https://doi.org/10.1016/j.ejor.2019.07.055

Ruiz, R., García-Díaz, J. C., & Maroto, C. (2007). Considering scheduling and preventive maintenance in the flowshop sequencing problem. Computers & Operations Research, 34(11), 3314–3330. https://doi.org/10.1016/j.cor.2005.12.007

Salmasnia, A., & Mirabadi-Dastjerd, D. (2017). Joint production and preventive maintenance scheduling for a single degraded machine by considering machine failures. Operations Research & Management Science, 25(3), 544–578. https://doi.org/10.1007/s11750-017-0445-4

Seif, J., Yu, A. J., & Rahmanniyay, F. (2018). Modelling and optimization of a bi-objective flow shop scheduling with diverse maintenance requirements. International Journal of Production Research, 56(9), 3204–3225. https://doi.org/10.1080/00207543.2017.1403660

Squires, R. R., & Hoffman, K. L. (2015). A military maintenance planning and scheduling problem. Optimization Letters, 9(8), 1675–1688. https://doi.org/10.1007/s11590-014-0814-y

Tonke, D., & Grunow, M. (2018). Maintenance, shutdown and production scheduling in semiconductor robotic cells. International Journal of Production Research, 56(9), 3306–3325. https://doi.org/10.1080/00207543.2018.1444809

Ustinovichius, L., Popov, V., Cepurnaite, J., Vilutienė, T., Samofalov, M., & Miedziałowski, C. (2018). BIM-based process management model for building design and refurbishment. Archives of Civil and Mechanical Engineering, 18, 1136–1149. https://doi.org/10.1016/j.acme.2018.02.004

Wu, X., Zhang, K., & Cheng, M. (2017). Computational method for optimal machine scheduling problem with maintenance and production. International Journal of Production Research, 55(6), 1791–1814. https://doi.org/10.1080/00207543.2016.1245451

Xiao, L., Song, S., Chen, X., & Coit, D. W. (2016). Joint optimization of production scheduling and machine group preventive maintenance. Reliability Engineering & System Safety, 146, 68–78. https://doi.org/10.1016/j.ress.2015.10.013

Yang, L., Ma, X., & Zhao, Y. (2017). A condition-based maintenance model for a three-state system subject to degradation and environmental shocks. Computers & Industrial Engineering, 105, 210–222. https://doi.org/10.1016/j.cie.2017.01.012

Yang, L., Zhao, Y., & Ma, X. (2019). Group maintenance scheduling for two-component systems with failure interaction. Applied Mathematical Modelling, 71, 118–137. https://doi.org/10.1016/j.apm.2019.01.036

Yin, H. Y., Liu, L. Z., & Yeh, J. S. (2017). A multi-objective scheduling optimization model considering product blockage and machine faults. International Journal of Simulation Modelling, 16(3), 506–516. https://doi.org/10.2507/IJSIMM16(3)CO12