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Stochastic Model for Integrated Preventive Maintenance Planning

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DOI: 10.23977/msom.2022.030307 | Downloads: 34 | Views: 728

Author(s)

Safiye Turgay 1, Samet Koç 1, Çiğdem Cebeci 1

Affiliation(s)

1 Department of Industrial Engineering, Sakarya University, Esentepe Kampüsü, Üniversite Cd., Kemalpaşa, Serdivan/Sakarya, 54050, Turkey

Corresponding Author

Safiye Turgay

ABSTRACT

Preventive maintenance planning management is modelled with stochastic approach. It is aimed to prevent stoppages and quality disorders due to disturbances, carriage and maintenance processes in production. Different maintenance policy alternatives were considered in order to develop and sustain more effective maintenance policies. The preventive maintenance process includes the cost of inspection and maintenance status, the cost of repair and other losses in the accidents with operator injuries and damage to the possible value of the situation. The stochastic model approach is applied for determine the possible period intervals of the machinery and equipment and the maintenance process analyzed and discussed in detail. The preventive maintenance approach in the maintenance planning process is aimed to develop a sustainable maintenance policy without any disturbance in the quality of production from any disturbance and disruption of the system in the long term. However, it is aimed to take preventive maintenance measures as well as to analyze the current system condition and predict future situations.

KEYWORDS

Stochastic Modelling, Preventive Maintenance, Maintenance Planning, Mathematical Modelling

CITE THIS PAPER

Safiye Turgay, Samet Koç, Çiğdem Cebeci, Stochastic Model for Integrated Preventive Maintenance Planning. Manufacturing and Service Operations Management (2022) Vol. 3: 59-67. DOI: http://dx.doi.org/10.23977/msom.2022.030307.

REFERENCES

[1] Zhu, H., Liu, F., Shao, X., Liu, Q., Deng, Y. (2011) A cost-based selective maintenance decision-making method for machining line, Qual Reliab Eng Int, 27 (2) pp. 191–201
[2] Jia, Q.-S. (2010) A structural property of optimal policies for multi-component maintenance problems IEEE Trans Autom Sci Eng, 7 (3), pp. 677–680
[3] Alimian, M., Saidi-Mehrabad, M.,  Jabbarzadeh, A. (2019)A robust integrated production and preventive maintenance planning model for multi-state systems with uncertain demand and common cause failures, Journal of Manufacturing Systems 50, 263–277
[4] Shahraki, A.F., Yadav, O.P., Vagiatzzis, C.(2020), Selective maintenance optimization for multi-state systems considering stochastically dependent components and stochastic imperfect maintenance actions, Reliability Engineering&System Safety, 196, 106738.
[5] Zhou, X., Huang,K., Xi, L., Lee, J.(2015) Preventive maintenance modeling for multi-component systems with considering stochastic failures and disassembly sequence, Reliability Engineering & System Safety, 142,  231-237
[6] Dao, C.D., Zuo, M.J. (2017) Selective maintenance of multi-state systems with structural dependence, Reliability Engineering and System Safety, 159, 184-196.
[7] Di, M., Dio, R. Iannone, S. Miranda and S. Riemma, (2013), A framework for the choice of the opportunistic maintenance policy in industrial contexts, IEEE International Conference on Industrial Engineering and Engineering Management,  pp. 1716-1720, doi: 10.1109/IEEM.2013.6962703.
[8] Pham, H., Wang, H. (2000) Optimal (τ, T) opportunistic maintenance of a k-out-of-n: G system with imperfect PM and partial failure, Naval Research Logistics (NRL), 47 (3), 223–239. 
[9] Hou, W., & Jiang, Z. (2013). An opportunistic maintenance policy of multi-unit series production system with consideration of imperfect maintenance. Applied Mathematics & Information Sciences, 7(1L), 283–290.
[10] Alrabghi, A., Tiwari, A. (2015) State of the art in simulation-based optimisation for maintenance systems, Computers & Industrial Engineering, 82, 167–182
[11] Triska, Y., Agostino, İ.C.R.S., Penna, P.M., Braghirolli, L.F., Frazzon, E.M. (2021) Integrated production and maintenance planning method with simulation-based optimization, IFAC-PapersOnLine, Volume 54, Issue 1, 349-354, ISSN 2405-8963,
[12] Chang, Q., Ni, J., Bandyopadhyay, P., Biller, S., Xiao, G., Maintenance opportunity planning system, Journal of Manufacturing Science and Engineering, 129 (3) (2007), pp. 661– B. 
[13] Dekker, R., Reliability Engineering and System Safety, 51, 229(1996)
[14] Portioli-Staudacher, A., Tantardini, M. (2012),"Integrated maintenance and production planning: a model to include rescheduling costs", Journal of Quality in Maintenance Engineering, Vol. 18, 1, 42 – 59
[15] Creţu, A., Peptan, E (2003), "Uncertainty and optimum portfolios", ASE Press, Bucharest
[16] Jonge, B., Scarf, P.A., A review on maintenance optimization, European Journal of Operational Research, Volume 285, Issue 3, 805-824,
[17] Gholizadeh, H., Chaleshigar, M., Fazlollahtabar, H.(2022) Robust optimization of uncertainty-based preventive maintenance model for scheduling series–parallel production systems (real case: disposable appliances production) ,ISA Transactions, Volume 128, Part B, pp. 54-67.
[18] Hillier, S.Frederick, Gerald J. Lieberman (2001), Introduction to Operations Research, 7th. Edition. McGraw-Hill, New York.
[19] Liu, Y., Chen, Y., Jiang, T. (2018) On Sequence Planning for Selective Maintenance of Multi-State Systems under Stochastic Maintenance Durations, European Journal of Operational Research, 268, 113-127.
[20] Pistikopolos, E.N., Vassiliadis, C.G., Arvela, J. and Papageorgiou, L.G. (2001), "Interactions of maintenance and production planning for multipurpose processplants – a system effectiveness approach", Industrial and Engineering Chemistry Research, Vol. 40, pp. 3195-207.
[21] Wang, N., Hu, J., Ma, L., Xiao, B., Liao, H. (2020) Availability Analysis and Preventive Maintenance Planning for Systems with General Time Distributions, Reliability Engineering and System Safety, 201, 106993.

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