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Abstrakty
In the marine industry, heave compensation systems are applied to marine equipment to compensate for the adverse effects of waves and the hydraulic system is usually used as the power system of heave compensation systems. This article introduces importance theory to the opportunistic maintenance (OM) strategy to provide guidance for the maintenance of heave compensation systems. The working principle of a semi-active heave compensation system and the specific working states of its hydraulic components are also first explained. Opportunistic maintenance is applied to the semi-active heave compensation system. Moreover, the joint integrated importance measure (JIIM) between different components at different moments is analyzed and used as the basis for the selection of components on which to perform PM, with the ultimate goal of delaying the degradation of the expected performance of the system. Finally, compared with conditional marginal reliability importance (CMRI)based OM, the effectiveness of JIIM-based OM is verified by the Monte Carlo method.
Czasopismo
Rocznik
Tom
Strony
512--521
Opis fizyczny
Bibliogr. 31 poz., rys., tab.
Twórcy
autor
- School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China
- Research Institute for Frontier Science, Beihang University, Beijing 100191, China
- Ningbo Institute of Technology, Beihang University, Ningbo 315800, China
autor
- School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China
- Ningbo Institute of Technology, Beihang University, Ningbo 315800, China
autor
- School of Management Engineering, Zhengzhou University, Zhengzhou 450001, China
autor
- School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China
- Ningbo Institute of Technology, Beihang University, Ningbo 315800, China
autor
- School of Automation Science and Electrical Engineering, Beihang University, Beijing 100083, China
autor
- Engineering Technology Department, Old Dominion University, Norfolk, VA 23529 USA
Bibliografia
- 1. Ahmad R, Kamaruddin S. An overview of time-based and condition-based maintenance in industrial application. Computers & Industrial Engineering 2012; 63: 135-149, https://doi.org/10.1016/j.cie.2012.02.002.
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- 3. Bukowski L, Werbińska-Wojciechowska S. Using fuzzy logic to support maintenance decisions according to Resilience-Based Maintenance concept. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2021; 23: 294-307, https://doi.org/10.17531/ein.2021.2.9.
- 4. Chen C, Wang C, Lu N, Jiang B, Xing Y. A data-driven predictive maintenance strategy based on accurate failure prognostics. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2021; 23: 387-394, https://doi.org/10.17531/ein.2021.2.19.
- 5. Chong A K W, Mohammed A H, Abdullah M N, Rahman M S. Maintenance prioritization - a review on factors and methods. Journal of Facilities Management 2019; 17 (1), 18-39, https://doi.org/10.1108/JFM-11-2017-0058.
- 6. Do K D, Pan J. Nonlinear control of an active heave compensation system. Ocean Engineering 2008; 35: 558-571, https://doi.org/10.1016/j.oceaneng.2007.11.005.
- 7. Dui H Y, Li S M, Xing L D, Liu H L. System performance-based joint importance analysis guided maintenance for repairable systems. Reliability Engineering & System Safety 2019; 186: 162-175, https://doi.org/10.1016/j.ress.2019.02.021.
- 8. Dui H Y, Si S B and Yam R C M. A cost-based integrated importance measure of system components for preventive maintenance. Reliability Engineering & System Safety 2017; 168: 98-104, https://doi.org/10.1016/j.ress.2017.05.025.
- 9. Gao X L, Cui, L R, Li J L. Analysis for joint importance of components in a coherent system. European Journal of Operational Research 2007; 182: 282-299, https://doi.org/10.1016/j.ejor.2006.07.022.
- 10. Golbasi O, Demirel N. Risk-based reliability allocation methodology to set a maintenance priority among system components: A case study in Mining. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2017; 19(2): 191-202, https://doi.org/10.17531/ein.2017.2.6.
- 11. Huynh K T, Barros A, Bérenguer C. Multi-Level Decision-Making for The Predictive Maintenance of k-Out-of-n: F Deteriorating Systems. IEEE Transactions on Reliability 2015; 64: 94-117, https://doi.org/10.1109/TR.2014.2337791.
- 12. Kuechler S, Mahl T, Neupert J, Schneider K, Sawodny O. Active Control for an Offshore Crane Using Prediction of the Vessel's Motion. IEEE/ASME Transactions on Mechatronics 2011; 16: 297-309, https://doi.org/10.1109/TMECH.2010.2041933.
- 13. Kumar V, Kumar G, Singh RK, Soni U. Degrading systems availability analysis: analytical semi-Markov approach. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2021; 23 (1): 195-208, https://doi.org/10.17531/ein.2021.1.20.
- 14. Kuo W, Zhu X. Relations and Generalizations of Importance Measures in Reliability. IEEE Transactions on Reliability 2012; 61: 956-674, https://doi.org/10.1109/TR.2012.2194196.
- 15. Kuo W, Zhu X. Some Recent Advances on Importance Measures in Reliability. IEEE Transactions on Reliability 2012; 61: 344-360, https://doi.org/10.1109/TR.2012.2194196.
- 16. Lee S H, Lee Y S, Kim J O. Decision of Maintenance Priority Order for Substation Facility through Structural Importance and Fault Analysis. Journal of the Korean Institute of Illuminating and Electrical Installation Engineers 2013; 27(4), 23-30, https://doi.org/10.5207/JIEIE.2013.27.4.023.
- 17. Li S Z, Wei J H, Guo K, Zhu W L. Nonlinear Robust Prediction Control of Hybrid Active-Passive Heave Compensator With Extended Disturbance Observer. IEEE Transactions on Industrial Electronics 2017; 64: 6684-6694, https://doi.org/10.1109/TIE.2017.2698358.
- 18. Lotovskyi E, Teixeira AP, Guedes Soares C. Availability analysis of an offshore oil and gas production system subjected to age-based preventive maintenance by Petri Nets. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22: 627-637, https://doi.org/10.17531/ein.2020.4.6.
- 19. Młynarski S, Pilch R, Smolnik M, Szybka J, Wiązania G. A model of an adaptive strategy of preventive maintenance of complex technical objects. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2020; 22: 35-41, https://doi.org/10.17531/ein.2020.1.5.
- 20. Nespoli A, Besseghini S, Pittaccio S, Villa E, Viscuso S. The high potential of shape memory alloys in developing miniature mechanical devices: A review on shape memory alloy mini-actuators. Sensors and Actuators A: Physical 2010; 158: 149-160, https://doi.org/10.1016/j.sna.2009.12.020.
- 21. Nguyen K A, Do P, Grall A. Condition-based maintenance for multi-component systems using importance measure and predictive information. International Journal of Systems Science: Operations & Logistics 2014; 1: 228-245, https://doi.org/10.1080/23302674.2014.983582.
- 22. Özcan E, Yumuşak R, Eren T. A novel approach to optimize the maintenance strategies: a case in the hydroelectric power plant. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2021; 23: 324-337, https://doi.org/10.17531/ein.2021.2.12.
- 23. Saleh N, Sharawi A A, Abd Elwahed M, et al. Preventive maintenance prioritization index of medical equipment using quality function deployment. IEEE Journal of Biomedical and Health Informatics 2014; 19(3): 1029-1035, https://doi.org/10.1109/JBHI.2014.2337895.
- 24. Si S, Dui H, Zhao X, Zhang S, Sun, S. Integrated importance measure of component states based on loss of system performance. IEEE Transactions on Reliability 2012; 61: 192-202, https://doi.org/10.1109/TR.2011.2182394.
- 25. Southerland JR. Mechanical systems for ocean engineering. Naval Engineers Journal 1970; 82: 63-74, https://doi.org/10.1111/j.1559-3584.1970.tb04361.x.
- 26. Tan CM, Na rula U, La i LA, Pandey S, Tung JH, Li CY. Optimal maintenance strategy on medical instruments used for haemodialysis process. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2019; 21: 318-328, https://doi.org/10.17531/ein.2019.2.17.
- 27. Wang H. A survey of maintenance policies of deteriorating systems. European Journal of Operational Research 2002; 139: 469-489, https://doi.org/10.1016/S0377-2217(01)00197-7.
- 28. Woodacre J K, Bauer R J, Irani R A. A review of vertical motion heave compensation systems. Ocean Engineering 2015; 104, 140-154, https://doi.org/10.1016/j.oceaneng.2015.05.004.
- 29. Wu, S. Joint importance of multistate systems. Computers & Industrial Engineering 2005; 49: 63-75, https://doi.org/10.1016/j.cie.2005.02.001.
- 30. Wu S, Chen Y, Wu Q, Wang, Z. Linking component importance to optimisation of preventive maintenance policy. Reliability Engineering & System Safety 2016; 146: 26-32, https://doi.org/10.1016/j.ress.2015.10.008.
- 31. Zhang C, Qian Y, Dui H, Wang S, Shi J. Component failure recognition and maintenance optimization for offshore heave compensation systems based on importance measures. Journal of Loss Prevention in the Process Industries 2020; 63, https://doi.org/10.1016/j.jlp.2019.103996.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-af3aaaf0-a507-449d-938a-dc6fd70e9f1f