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Vol.2, No.4, 2023: pp.151-160
Application of the multicriteria decision-making for selecting optimal maintenance strategy
Authors:
Sanja Simić1
, Mijodrag Milošević2
, Borut Kosec3
, Dejan Božić2
, Dejan Lukić2
1Continental Automotive Serbia d.o.o., Novi Sad, Serbia
2University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia
3University of Ljubljana, Faculty of Natural Science and Engineering, Ljubljana, Slovenia
Received: 26 June 2023
Revised: 10 September 2023
Accepted: 11 October 2023
Published: 31 December 2023
Abstract:
Assessing the best set of maintenance guidelines for various types of failures is often a challenging and complex task. It requires understanding various factors such as safety aspects, environmental issues, energy savings, costs, budget constraints, system reliability, resource utilization, and more. Implementing the correct maintenance process is a critical step in production to increase reliability and improve the effectiveness and quality of the production system. Despite the significant importance of this issue, there are not many studies that analyse and develop procedures for selecting the optimal maintenance strategy. This paper presents the selection of the optimal maintenance strategy using multicriteria decision-making, specifically the Analytic Hierarchy Process (AHP), for a case study involving a company in the automotive industry. The defined alternatives are the four most commonly used machine maintenance strategies in the industry: corrective, preventive, condition- based maintenance, and total productive maintenance. The decision criteria considered in the analysis are: production quality, reliability, costs, and safety, along with their respective sub-criteria.
Keywords:
Multicriteria decision making, AHP, maintenance, reliability, production quality, safety, costs
References:
[1] T. Nakagawa, Maintenance Theory of Reliability. Springer, London, 2005. https://doi.org/10.1007/1-84628-221-7
[2] E. Ruschel, E.A.P. Santos, E. de F.R. Loures, Industrial maintenance decision-making: A systematic literature review. Journal of Manufacturing Systems, Society of Manufacturing Engineers, 45, 2017: 180-194.
https://doi.org/10.1016/j.jmsy.2017.09.003
[3] M. Bevilacqua, M. Braglia, The analytic hierarchy process applied to maintenance strategy selection. Reliability Engineering and System Safety, 70(1), 2000: 71-83. https://doi.org/10.1016/S0951-8320(00)00047-8
[4] L. Wang, J. Chu, J. Wu, Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process. International Journal of Production Economics, 107(1), 2007: 151-163. https://doi.org/10.1016/j.ijpe.2006.08.005
[5] M. Nikolić, Lj. Radovanović, E. Desnica, J. Pekez, The application of VIKOR method for selection of maintenance strategies. Technical Diagnostics, 9(4), 2010: 25-32.
[6] I. Gertsbakh, Reliability theory with applications to preventive maintenance. Springer, Berlin, 2000.
https://doi.org/10.1007/978-3-662-04236-6
[7] A.T. de, Almeide, R.J.P. Ferreira, C.A.V. Cavalcante, A review of the use of multicriteria and multi-objective models in maintenance and reliability. IMA Journal of Management Mathematics, 26(3), 2015: 249- 271.
https://doi.org/10.1093/imaman/dpv010
[8] F.J.C. de, Melo, J.V. Sousa, J.T. de, Aquino, T. de B. Jerônimo, Using AHP to improve manufacturing processes in TPM on industrial and port complex. American Psychological Association (APA), 19(3), 2021: 523-549.
https://doi.org/10.5585/exactaep.2021.16693
[9] N. Stanković, Risk-based maintenance models and their impact on steam turbine reliability, (Ph.D. Thesis). Technical faculty ”Mihajlo Pupin”, University of Novi Sad, Zrenjanin, Serbia, 2018.
[10] A.A. Muhsen, G.M. Szymanski, T.A. Mankhi, B. Attiya, Selecting the most efficient maintenance approach using AHP multiple criteria decision making at Haditha hydropower plant. Zeszyty naukowe politechniki poznańskiej, 78, 2018: 113-136. https://doi.org/10.21008/j.0239-9415.2018.078.09
[11] L.M.D.F. Ferreira, I. Maganha, V.S.M. Magalhães, M. Almeida, A multicriteria Decision Framework for the Management of Maintenance Spares – A Case Study. IFAC PapersOnLine, 51(11), 2018: 531-537.
https://doi.org/10.1016/j.ifacol.2018.08.373
[12] K. Velmurugan, S. Saravanasankar, P. Venkumar, R. Sudhakarapandian, G.D. Bona, Hybrid fuzzy AHP-TOPSIS framework on human error factor analysis: Implications to developing optimal maintenance maintenance management system in the SMEs. Sustainable Futures, 4, 2022: 100087. https://doi.org/10.1016/j.sftr.2022.100087
[13] D. Prabhakar, A. Dharmaraj, Modern Plant Maintenance and Reliability Management Methods – A Review. International Journal of Mechanical and Production Engineering Research and Development, 8(3), 2018: 791-802.
https://doi.org/10.24247/ijmperdjun201883
[14] D. Lukic, M. Milosevic, A. Antic, S. Borojevic, M. Ficko, Multi-criteria selection of manufacturing processes in the conceptual process planning. Advances in Production Engineering & Management, 12(2), 2017: 151-162.
https://doi.org/10.14743/apem2017.2.247
[15] A. Aytekin, Energy, Environment, and Sustainability: A Multi-criteria Evaluation of Countries. Strategic Planning for Energy and the Environment, 41(3), 2022: 281-316. https://doi.org/10.13052/spee1048-5236.4133
[16] G. Marinković, T. Ninkov, M Trifković, Ž. Nestorović, G. Pejičić, On the land consolidation projects and cadastral municipalities ranking. Tehnički vjesnik, 23(4), 2016: 1147-1153. https://doi.org/10.17559/TV-20140316225250
[17] M. Madić, G. Petrović, D. Petković, J. Antucheviciene, D. Marinković, Application of a Robust Decision-Making Rule for Comprehensive Assessment of Laser Cutting Conditions and Performance. Machines, 10(2), 2022: 153.
https://doi.org/10.3390/machines10020153
[18] M. Köksalan, J. Wallenius, S. Zionts, Multiple Criteria Decision Making: From Early History to the 21st Century. World Scientific Publishing, Singapore. 2011. https://doi.org/10.1142/8042
[19] A. Ishizaka, P. Nemery, Multi-Criteria Decision Analysis: Methods and Software. John Wiley & Sons, Hoboken, 2013. http://dx.doi.org/10.1002/9781118644898
[20] D. Lukic, R. Cep, J. Vukman, A. Antic, M. Djurdjev, M. Milosevic, Multi-Criteria Selection of the Optimal Parameters for High-Speed Machining of Aluminum Alloy Al7075 Thin-Walled Parts. Metals, 10(12), 2020: 1570.
https://doi.org/10.3390/met10121570
[21] E.C. Özcan, S. Ünlüsoy, T. Eren, A combined goal programming – AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants. Renewable and Sustainable Energy Reviews, 78, 2017: 1410-1423. https://doi.org/10.1016/j.rser.2017.04.039
[22] I. Vinogradova, Multi-attribute decision-making methods as a part of mathematical optimization. Mathematics, 7(10), 2019: 915. https://doi.org/10.3390/math7100915
[23] T.L. Saaty, The Analytic Hierarchy Process: planning, priority setting, resource allocation. McGraw-Hill, New York, USA, 1980.
[24] M. Bertolini, M. Bevilacqua, A combined goal programming – AHP approach to maintenance selection problem. Reliability Engineering and System Safety, 91(7), 2006: 839-848. https://doi.org/10.1016/j.ress.2005.08.006
[25] G.-H. Tzeng, J.-J. Huang, Multiple Attribute Decision Making: Methods and Applications. Chapman and Hall/CRC, New York, USA, 2011. https://doi.org/10.1201/b11032
[26] C.A.B. Costa, M.C. Carnero, M.D. Oliveira, A multi-criteria model for auditing a Predictive Maintenance Programme. European Journal of Operational Research, 217(2), 2012: 381-393. https://doi.org/10.1016/j.ejor.2011.09.019
[27] M. Milošević, D. Lukić, G. Ostojić, M. Lazarević, A. Antić, Application of cloud-based machine learning in cutting tool condition monitoring. Journal of Production Engineering, 25(1), 2022: 20-24.
[28] Z.T. Xiang, C.J. Feng, Implementing total productive maintenance in a manufacturing small or medium-sized enterprise. Journal of Industrial Engineering and Management, 14(2), 2021: 152-175. https://doi.org/10.3926/jiem.3286
[29] M. Kannan, S. Singh, R.R. Prasad, Synthetic methods to obtain calcia-stabilized zirconia powders: a review. In: G. Manik, S. Kalia, S.K. Sahoo, T.K. Sharma, O.P. Verma, (eds). Advances in mechanical engineering: Lecture notes in mechanical engineering. Springer, Singapore, 2021: 405-416. https://doi.org/10.1007/978-981-16-0942-8_39
© 2023 by the authors. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
Volume 3
Number 2
June 2024.
How to Cite
S. Simić, M. Milošević, B. Kosec, D. Božić, D. Lukić, Application of the Multicriteria Decision-Making for Selecting Optimal Maintenance Strategy. Advanced Engineering Letters, 2(4), 2023: 151-160.
https://doi.org/10.46793/adeletters.2023.2.4.3
More Citation Formats
Simić, S., Milošević, M., Kosec, B., Božić, D., & Lukić, D. (2023). Application of the Multicriteria Decision-Making for Selecting Optimal Maintenance Strategy. Advanced Engineering Letters, 2(4), 151-160.
https://doi.org/10.46793/adeletters.2023.2.4.3
Simić, Sanja, et al. ”Application of the Multicriteria Decision-Making for Selecting Optimal Maintenance Strategy.” Advanced Engineering Letters, vol. 2, no. 4, 2023, pp. 151-160.
https://doi.org/10.46793/adeletters.2023.2.4.3
Simić, Sanja Mijodrag Milošević, Borut Kosec, Dejan Božić, and Dejan Lukić. 2023. “Application of the Multicriteria Decision-Making for Selecting Optimal Maintenance Strategy.“ Advanced Engineering Letters, 2 (4): 151-160.
https://doi.org/10.46793/adeletters.2023.2.4.3.
Simić, S., Milošević, M., Kosec, B., Božić, D., and Lukić, D. (2023). Application of the Multicriteria Decision-Making for Selecting Optimal Maintenance Strategy. Advanced Engineering Letters, 2(4), pp.151-160.
doi: 10.46793/adeletters.2023.2.4.3.