Int J Performability Eng ›› 2021, Vol. 17 ›› Issue (9): 766-778.doi: 10.23940/ijpe.21.09.p3.766778
Previous Articles Next Articles
Ruiqi Wang, Guangyu Chen*, Na Liang, Zheng Huang
Submitted on
;
Revised on
;
Accepted on
Contact:
* E-mail address: chenguangyu@uestc.edu.cn
Ruiqi Wang, Guangyu Chen, Na Liang, Zheng Huang. Preventive Maintenance Optimization Regarding Large-Scale Systems based on the Life-Cycle Cost [J]. Int J Performability Eng, 2021, 17(9): 766-778.
Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks
[1] Mahmoud M.S.Multilevel systems control and applications: a survey. [2] Ko, Y.M. and Byon, E.Reliability evaluation of large-scale systems with identical units. [3] Chen G., Zhang W., Li J., andLiu Y,Optimization modeling of system lifecycle costs with reliability constraints under Weibull distribution. In [4] Yang L., Zhao Y., andX, M. Grouping maintenance scheduling for two-component systems with failure interaction. Applied Mathematical Modelling, 71(7), pp. 118-137, 2019. [5] Thomas L.C.A survey of maintenance and replacement models for maintainability and reliability of multi-item systems. [6] Castanier B., Grall A., andBérenguer C.A condition-based maintenance policy with non-periodic inspections for a two-unit series system. [7] Vijayan, V. and Chaturvedi, S.K.Multi-component maintenance grouping optimization based on stochastic dependency. [8] Wang H.A survey of maintenance policies of deteriorating systems. [9] Okoh P.Maintenance grouping optimization for the management of risk in offshore riser system. [10] Hameed, Z. and Vatn, J.How to develop the grouping strategy for offshore wind turbines at the wind farm level. In [11] Sun Y., Kang J., Sun L., Jin P., andBai X.Condition-based maintenance for the offshore wind turbine based on long short-term memory network. [12] Rokstad, M.M. and Ugarelli, R.M.Minimising the total cost of renewal and risk of water infrastructure assets by grouping renewal interventions. [13] Finkelstein M., Cha J.H., andLevitin G.On a new age‐replacement policy for items with observed stochastic degradation. [14] Van Horenbeek, A. and Pintelon, L. A dynamic predictive maintenance policy for complex multi-component systems. [15] Le, M.D. and Tan, C.M.Optimal maintenance strategy of deteriorating system under imperfect maintenance and inspection using mixed inspectionscheduling. [16] Nguyen D.T., Dijoux Y., andFouladirad M.Analytical properties of an imperfect repair model and application in preventive maintenance scheduling. [17] Li Z.Q., Xu T.X., Gu J.Y., Fu L.Y., andAn J.Optimal maintenance policies for series systems under imperfect repair considering aging factor. [18] Zequeira, R.I. and Bérenguer, C.Periodic imperfect preventive maintenance with two categories of competing failure modes. [19] Huynh K.T., Castro I.T., Barros A., andBérenguer C.Modeling age-based maintenance strategies with minimal repairs for systems subject to competing failure modes due to degradation and shocks. [20] El-Ferik, S. Economic production lot-sizing for an unreliable machine under imperfect age-based maintenance policy. [21] Gilardoni G.L., de Toledo, M.L.G., Freitas, M.A., and Colosimo, E.A. Dynamics of an optimal maintenance policy for imperfect repair models. [22] Yang L., Ye Z.S., Lee C.G., Yang S.F., andPeng R.A two-phase preventive maintenance policy considering imperfect repair and postponed replacement. [23] Wu T., Ma X., Yang L., andZhao Y.Proactive maintenance scheduling in consideration of imperfect repairs and production wait time. [24] Mullor R., Mulero J., andTrottini M.A modelling approach to optimal imperfect maintenance of repairable equipment with multiple failure modes. [25] Niu C., Jiang J., Ge B., andChen Y.Preventive maintenance model based on the renewal-geometric process. [26] Taghipour S., Banjevic D., andJardine A.K.Periodic inspection optimization model for a complex repairable system. [27] Park J.H., Lee S.C., Hong J.W., andLie C.H.An optimal block preventive maintenance policy for a multi-unit system considering imperfect maintenance. [28] Jin-He, W., Xiao-Hong, Z., and Jian-Chao, Z. Optimal maintenance decision for wind turbines based on imperfect maintenance model. [29] Öner K.B., Kiesmüller G.P., andvan Houtum, G.J. Optimization of component reliability in the design phase of capital goods. [30] Tian, Z. and Zuo, M.J.Redundancy allocation for multi-state systems using physical programming and genetic algorithms. [31] Micheli L., Cao L., Laflamme S., andAlipour A.Life-cycle cost evaluation strategy for high-performance control systems under uncertainties. [32] Carretero J., Pérez J.M., Garcia-Carballeira, F., Calderón, A., Fernández, J., Garcia, J.D., Lozano, A., Cardona, L., Cotaina, N., and Prete, P. Applying RCM in large scale systems: a case study with railway networks. [33] Tian Z., Levitin G., andZuo M.J.A joint reliability-redundancy optimization approach for multi-state series-parallel systems. [34] Zhao X., Fouladirad M., Bérenguer C., andBordes L.Condition-based inspection/replacement policies for non-monotone deteriorating systems with environmental covariates. [35] Nourelfath M., Châtelet E., andNahas N.Joint redundancy and imperfect preventive maintenance optimization for series-parallel multi-state degraded systems. [36] Levitin, G. and Lisnianski, A.A new approach to solving problems of multi‐state system reliability optimization. [37] Coit, D.W. and Smith, A.E.Genetic algorithm to maximize a lower-bound for system time-to-failure with uncertain component Weibull parameters. [38] Li. J, Chen. G, Tang, L, et al. Availability model and redundancy design optimization of bi level polymorphic weighted k/ n system, [39] Tian, Z. and Liao, H.Condition based maintenance optimization for multi-component systems using proportional hazards model. [40] Ko, Y.M. and Byon, E.Condition-based joint maintenance optimization for a large-scale system with homogeneous units. [41] Chen, G., Zhang, W,Zhang, X, System life cycle cost modeling and decision making under Weibull distribution, [42] Zhao X., Gao C., Qian C., andNakagawa T.Approximate calculations of age-based random replacement times. [43] Sanoubar S., He K., Maillart L.M., andProkopyev O.A.Optimal Age-Replacement in Anticipation of Time-Dependent, Unpunctual Policy Implementation.IEEE Transactions on Reliability, 2020. [44] Wang R., Chen G., andLiang N.Preventive maintenance optimization for large-scale systems under life cycle cost. In [45] Blanchard B. S.Design and manage to life cycle cost.Barringer & Associates Inc.p.o.box, 1997. [46] Cai Y.Z., Liu L., Cheng H.Z., Ma Z.L., andZhu Z.L.Application review of life cycle cost(LCC) technology in power system. [47] Mettas A.Reliability allocation and optimization for complex systems. In [48] Jin, T. and Wang, P.Planning performance based contracts considering reliability and uncertain system usage. [49] Cherkaoui H., Huynh K.T., andGrall A.Quantitative assessments of performance and robustness of maintenance policies for stochastically deteriorating production systems. |
[1] | Tyler D. Ridder and Ram M. Narayanan. Radar Detection Performability under Graceful Degradation [J]. Int J Performability Eng, 2021, 17(8): 666-675. |
[2] | S. Anbazhagan, and S. Karthikumar. Multilevel Image Threshold Estimation using Teaching Learning-based Optimization [J]. Int J Performability Eng, 2021, 17(7): 638-646. |
[3] | D.P. Tripathi, Mahesh Nayak, Rajaboina Manoj, Surarapu Sudheer, and K. Praghash. Fast Computational Efficient Directional Shrinking Search Optimization Algorithm [J]. Int J Performability Eng, 2021, 17(6): 543-551. |
[4] | Ngangbam Phalguni Singh, Sabbisetty Akhil, Ratakonda Vishnu, K. Kirit Redddy, B. Bhanu Prakash, and Shruti Suman. Investigation of Growth Management and Field Optimization on IOT-based Technology for Chilli Cultivation: Hybrid Chilli (F1 Golden Parrot) in Pallavolu, Nellore [J]. Int J Performability Eng, 2021, 17(6): 559-568. |
[5] | Fatma Zohra Labadlia, Elias Hadjadj Aoul, Brahim Hamaidi, and Mohammed Bougofa. Optimization of Safety Instrumented System Configuration based on Simplex Algorithm [J]. Int J Performability Eng, 2021, 17(2): 191-199. |
[6] | Bouzouada Abdallah, Yssaad Benyssaad, Daoud Mohamed, Bekkouche Benaissa, and Yagoubi Benabdellah. Maintenance Optimization for Complex System using Evolutionary Algorithms under Reliability Constraints within the Context of the Reliability-Centered-Maintenance [J]. Int J Performability Eng, 2021, 17(1): 1-13. |
[7] | Kun Li, Liwei Jia, and Xiaoming Shi. IPSOMC: An Improved Particle Swarm Optimization and Membrane Computing based Algorithm for Cloud Computing [J]. Int J Performability Eng, 2021, 17(1): 135-142. |
[8] | Xiu Kan, Xiafeng Zhang, Le Cao, Dan Yang, and Yixuan Fan. EMG Pattern Recognition based on Particle Swarm Optimization and Recurrent Neural Network [J]. Int J Performability Eng, 2020, 16(9): 1404-1415. |
[9] | Ran Zhang, Min Liu, Yifeng Yin, Qikun Zhang, and Zengyu Cai. Prediction Algorithm for Network Security Situation based on BP Neural Network Optimized by SA-SOA [J]. Int J Performability Eng, 2020, 16(8): 1171-1182. |
[10] | Shujun Pei, Qinggen Zhang, and Xuehui Cheng. Workflow Scheduling using Graph Segmentation and Reinforcement Learning [J]. Int J Performability Eng, 2020, 16(8): 1262-1270. |
[11] | Manish Rawat and Bhupesh Kumar Lad. Joint Optimization of Reliability Design and Level of Repair Analysis Considering Time Dependent Failure Rate of Fleet System [J]. Int J Performability Eng, 2020, 16(6): 821-833. |
[12] | Shenyi Qian, Yongsheng Shi, Huaiguang Wu, and Songtao Shang. Prediction of Electricity Tariff Recovery Risk based on Hybrid Feature Selection Algorithm [J]. Int J Performability Eng, 2020, 16(6): 846-854. |
[13] | Hongchan Li and Haodong Zhu. Modified Water Wave Optimization for Energy-Conscious Dual-Resource Constrained Flexible Job Shop Scheduling [J]. Int J Performability Eng, 2020, 16(6): 916-929. |
[14] | Yong Cui, Haoran Chen, and Liang Zhu. Improved Post-Copy Live Migration with Memory Page Prefetching [J]. Int J Performability Eng, 2020, 16(5): 728-737. |
[15] | Xuan Chen, Zhengjiang Song, Hongfeng Zheng, and Zhiping Wan. Task Scheduling based on Fruit Fly Optimization Algorithm in Mobile Cloud Computing [J]. Int J Performability Eng, 2020, 16(4): 618-628. |
|