Optimal maintenance policy for a Markov deteriorating system under reliability limit

• Autorzy: Kocer Ozturk Meltem , Khaniyev Tahir

Identyfikatory

DOI

10.17531/ein/190865

• Języki publikacji: EN

Abstrakty

EN

In this study, failure data of computer numerical control machine used in defense industry was analyzed to develop maintenance algorithm with a Markov feature. An imperfect preventive maintenance model that minimizes long-term operational cost is created for the machine wearing down randomly over time. The reliability-centric preventive maintenance policy was developed where the system status was monitored instantaneously. The use and age-related deterioration process of system is defined as the failure rate increase factor and age reduction factor, and these variables are combined to create hybrid failure model. As result of the imperfect maintenance algorithm developed for the multi-component machine, minimum long-term total unit cost, optimum system reliability value, number of maintenance and times between sequential maintenance cycles are obtained as outputs. Furthermore, system sub-equipment was specified that needs to be maintained in each cycle. Moreover, imperfect maintenance activities are planned when the reliability level of subsystems drops to the predetermined R value.

Słowa kluczowe

EN

preventive maintenance; imperfect maintenance; age-related deterioration; optimization; reliability

• Wydawca: Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne
• Czasopismo: Eksploatacja i Niezawodność
• Rocznik: 2024
• Tom: Vol. 26, no. 4
• Strony: art. no. 190865
• Opis fizyczny: Bibliogr. 38 poz., rys., tab., wykr.

Twórcy

autor

Kocer Ozturk Meltem

• Product Assurance Department, Turkish Aerospace, Turkey

autor

Khaniyev Tahir

• Department of Industrial Engineering, TOBB University of Economics and Technology, Turkey
• The Center of Digital Economics, Azerbaijan State University of Economics, Azerbaijan

• https://orcid.org/0000-0003-1974-0140

Bibliografia

• 1. Barlow R E, Proschan F. Mathematical theory of reliability, Society for Industrial and Applied Mathematics, Philadelphia 1996; https://doi.org/10.1137/1.9781611971194.
• 2. Block H W, Borges W S, Savits T H. Age-dependent minimal repair, Journal of Applied Probability 1985; 22(2), 370-385, https://doi.org/10.2307/3213780
• 3. Boland P J. Periodic replacement when minimal repair costs vary with time, Naval Research Logistics 1982; 29, 541-546, https://doi.org/10.1002/nav.3800290402
• 4. Chan G K, Asgarpoor S. Optimum maintenance policy with Markov processes, Electric Power Systems Research 2006; 76, 452-456, https://doi.org/10.1016/j.epsr.2005.09.010
• 5. Chan F T S, Lau H C W, Ip R W L, Chan H K, Kong S. Implementation of Total Productive Maintenance: A Case Study, International Journal of Production Economics 2005; 95, 71-94, https://doi.org/10.1016/j.ijpe.2003.10.021
• 6. Chiang J H, Yuan J. Optimal maintenance policy for a Markovian system under periodic inspection, Reliability Engineering and System Safety 2001; 71, 165-172, https://doi.org/10.1016/S0951-8320(00)00093-4
• 7. Coria V H, Maximov S, Rivas-Davalos F, Melchor C L, Guardado J L. Analytical method for optimization of maintenance policy based on available system failure data, Reliability Engineering and System Safety 2015; 135, 55-63, https://doi.org/10.1016/j.ress.2014.11.003
• 8. Das K, Lashkari R S, Sengupta S. Machine reliability and preventive maintenance planning for cellular manufacturing systems, European Journal of Operational Research 2007; 183, 162-180, https://doi.org/10.1016/j.ejor.2006.09.079
• 9. Dong W, Liu S, Yang X, Wang H, Fang Z. Balancing reliability and maintenance cost rate of multi-state components with fault interval omission, Eksploatacja i Niezawodnosc – Maintenance and Reliability 2019;21(1):37–45, https://doi.org/10.17531/ein.2019.1.5
• 10. Dongwei G, Ruihua N, Wenbo H, Guang C, Ligang J. Research on preventive maintenance strategy of Coating Machine based on dynamic failure rate, Eksploatacja i Niezawodnosc – Maintenance and Reliability 2023;25(1):20, https://doi.org/10.17531/ein.2023.1.20
• 11. Fan H, Hu C, Chen M, Zhou D. Cooperative predictive maintenance of repairable systems with dependent failure modes and resource constraint. IEEE Transactions on Reliability 2011; 60(1): 144-157, https://doi.org/10.1109/TR.2011.2104432
• 12. Gurler U, Kaya A. A maintenance policy for a system with multi-state components: an approximate solution, Reliability Engineering and System Safety 2002; 76, 117-127, https://doi.org/10.1016/S0951-8320(01)00125-9
• 13. Jiang L, Li B, Hu J. Preventive replacement policy of a system considering multiple maintenance actions upon a failure, Quality and Reliability Engineering International 2022; 1-14 , https://doi.org/10.1002/qre.3108
• 14. Khaniyev T, Baskir MB, Gokpinar F, Mirzayev F. Statistical distributions and reliability functions with type-2 fuzzy parameters, Eksploatacja i Niezawodnosc – Maintenance and Reliability 2019; 21(2), 268-274, https://doi.org/10.17531/ein.2019.2.11
• 15. Khatab A. Hybrid hazard rate model for imperfect preventive maintenance of systems subject to random deterioration, Journal of Intelligent Manufacturing 2013; https://doi.org/10.1007/s10845-013-0819-x
• 16. Kolhatkar A, Pandey A. Predictive maintenance methodology in sheet metal progressive tooling: a case study, International Journal of System Assurance Engineering and Management 2022; 14, 980-989, https://doi.org/10.1007/s13198-021-01564-3
• 17. Kozłowski E, Mazurkiewicz D, Żabiński T, Prucnal S, Sęp J. Machining sensor data management for operation-level predictive model. Expert Systems with Applications 2020; 159, https://doi.org/10.1016/j.eswa.2020.113600
• 18. Kumaresan V, Saravanasankar S, Di Bona G. Identification of optimal maintenance parameters for the best maintenance and service management system in the SMEs, Journal of Quality in Maintenance Engineering 2024; 30(1), pp.133-152, https://doi.org/10.1108/JQME-10-2022-0070
• 19. Li YL, Zhang XG, Ran Y, Zhang GB. Reliability modeling and analysis for CNC machine tool based on meta‐action, Quality and Reliability Engineering International 2020; https://doi.org/10.1002/qre.2806
• 20. Liao W, Pan E, Xi L. Preventive maintenance scheduling for repairable system with deterioration, Journal of Intelligent Manufacturing 2010; 21, 875-884, https://doi.org/10.1007/s10845-009-0264-z
• 21. Lie C H, Chun Y H. An Algorithm for Preventive Maintenance Policy, IEEE Transactions on Reliability 1986; 35, 71-75, https://doi.org/10.1109/TR.1986.4335352
• 22. Lin Z, Huang Y, Fang C. Non-periodic preventive maintenance with reliability thresholds for complex repairable systems, Reliablity Engineering and System Safety 2015; 136, 145-156, https://doi.org/10.1016/j.ress.2014.12.010
• 23. Malik M A K. Reliable Preventive Maintenance Scheduling, American Institute of Industrial Engineers 1979; 11(3), 221-228, https://doi.org/10.1080/05695557908974463
• 24. Naderkhani F, Makis V. Optimal condition-based maintenance policy for a partially observable system with two sampling intervals, The International Journal of Advanced Manufacturing Technology 2014; 78, 795-805, https://doi.org/ 10.1007/s00170-014-6651-4
• 25. Nakagawa T. Modified discrete preventive maintenance policies, Naval Research Logistics 1986; 33, 703-715, https://doi.org/10.1002/nav.3800330413
• 26. Nakagawa T. Sequential imperfect preventive maintenance policies, IEEE Transactions on Reliability 1988; 37 (3), 295–298, https://doi.org/10.1109/24.3758
• 27. Noortwijk J M, Klatter H E. Optimal inspection decisions for the block mats of Eastern-Scheldt barrier, Reliabilty Engineering and System Safety 1999; 65, 203-211, https://doi.org/10.1016/S0951-8320(98)00097-0
• 28. Raza A, Ulansky V. Probabilistic indicators of imperfect inspections used in modeling condition-based and predictive maintenance, Journal of Risk and Reliability 2022; 237, https://doi.org/10.1177/1748006X221136317
• 29. Sobaszek L, Gola A, Swic A. Time-based machine failure prediction in multi-machine manufacturing systems, Eksploatacja i Niezawodnosc – Maintenance and Reliability 2020;22(1):52–62, https://doi.org/10.17531/ein.2020.1.7
• 30. Vaurio J K. Availability and cost functions for periodically inspected preventively maintained units, Reliability Engineering and System Safety 1999; 63, 133-140, https://doi.org/10.1016/S0951-8320(98)00030-1
• 31. Velmurugan K, Saravanasankar S, Venkumar P, Sudhakarapandian R, Di Bona G. Availability analysis of the critical production system in SMEs using the Markov decision model, Mathematical Problems in Engineering 2022; 2022, 1-16, https://doi.org/10.1155/2022/6026984
• 32. Velmurugan K, Saravanasankar S, Venkumar P, Paranitharan KP and Sudhakarapandian R. Industry 4.0: smart preventive maintenance with optimal planning and scheduling process of the SMEs, International Journal of Value Chain Management 2023; 14(1), pp.12-33, https://doi.org/10.1504/IJVCM.2023.10045444
• 33. Velmurugan K, Venkumar P, Sudhakarapandian R. Performance analysis of tyre manufacturing system in the SMEs using RAMD approach, Mathematical Problems in Engineering 2021; pp.1-14, https://doi.org/10.1155/2021/6616037
• 34. Velmurugan K, Venkumar P and Sudhakarapandian R. Design of optimal maintenance policy using Markov model, International Journal of Engineering and Advanced Technology 2019; 9(1S4), pp.907-917, https://doi.org/10.35940/ijeat.A1068.1291S419
• 35. Velmurugan K, Venkumar P, Sudhakarapandian R. Reliability availability maintainability analysis in forming industry, International Journal of Engineering and Advanced Technology 2019; 9(1S4), pp.822-828, https://doi.org/ 10.35940/ijeat.A1049.1291S419
• 36. Wang H, Pham H. Some maintenance models and availability with imperfect maintenance in production systems, Annals of Operation Research 1999; 91, 305–318, https://doi.org/10.1023/A:1018910109348
• 37. Wang J, Makis V, Zhao X. Optimal condition-based and age-based opportunistic maintenance policy for a two-unit series system, Computers and Industrial Engineering 2019; 134, 1-10, https://doi.org/10.1016/j.cie.2019.05.020
• 38. Wang W. An inspection model based on a three-stage failure process, Reliability Engineering and System Safety 2011; 96, 838–848, https://doi.org/10.1016/j.ress.2011.03.003