Jardine A K S, Lin D M, Banjevic D. A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 2006, 20(7): 1483-1510
[2]
Brombacher A. Reliability prediction and "Deepwater Horizon"; lessons learned. Quality and Reliability Engineering International, 2010, 26(5): 397
Wang H, Chai T Y, Ding J L, Brown M. Data driven fault diagnosis and fault tolerant control: some advances and possible new directions. Acta Automatica Sinica, 2009, 35(6): 739-747
[5]
Zhou Dong-Hua, Xu Zheng-Guo. A survey on real-time reliability evaluation and prediction techniques for engineering systems. Aerospace Control and Application, 2008, 34(4): 3-10(周东华, 徐正国. 工程系统的实时可靠性评估与预测技术. 空间控制技术与应用, 2008, 34(4): 3-10)
[6]
Zio E. Reliability engineering: old problems and new challenges. Reliability Engineering and System Safety, 2009, 94(2): 125-141
[7]
Li Gang. Quality Related Fault Diagnosis and Prognosis for Industrial Processes [Ph.D. dissertation], Tsinghua University, China, 2010(李钢. 工业过程质量相关的故障诊断与预测方法 [博士学位论文], 清华大学, 中国, 2010)
[8]
Sikorskaa J Z, Hodkiewicz M, Ma L. Prognostic modelling options for remaining useful life estimation by industry. Mechanical Systems and Signal Processing, 2011, 25(5): 1803-1836
[9]
Chen Xue-Chu. Modern Maintenance Theory. Beijing: National Defence Industry Press, 2003(陈学楚. 现代维修理论. 北京: 国防工业出版社, 2003)
[10]
Polunchenko A S, Tartakovsky A G. State-of-the-art in sequential change-point detection. Methodology and Computing in Applied Probability, 2012, 14(3): 649-684
[11]
Wang W B. A model to predict the residual life of rolling element bearings given monitored condition information to date. IMA Journal of Management Mathematics, 2002, 13(1): 3-16
[12]
Wang W B. A two-stage prognosis model in condition based maintenance. European Journal of Operational Research, 2007, 182(3): 1177-1187
[13]
Ng T S A. An application of the EM algorithm to degradation modeling. IEEE Transactions on Reliability, 2008, 57(1): 2-13
[14]
Yuan T, Kuo Y. Bayesian analysis of hazard rate, change point, and cost-optimal burn-in time for electronic devices. IEEE Transactions on Reliability, 2010, 59(1): 132-138
[15]
Woodall W H. Controversies and contradictions in statistical process control. Journal of Quality Technology, 2000, 32(4): 341-350
[16]
Bersimis S, Psarakis S, Panaretos J. Multivariate statistical process control charts: an overview. Quality and Reliability Engineering International, 2006, 23(5): 517-543
[17]
Tagaras G. An integrated cost model for the joint optimization of process control and maintenance. Journal of the Operational Research Society, 1988, 39(8): 757-766
[18]
Yeung T G, Cassady C R, Schneider K. Simultaneous optimization of X control chart and age-based preventive maintenance policies under an economic objective. IIE Transactions, 2007, 40(2): 147-159
[19]
Ben-Daya M, Rahim M A. Effect of maintenance on the economic design of x-control chart. European Journal of Operational Research, 2000, 120(1): 131-143
[20]
Wang W. Maintenance models based on the np control charts with respect to the sampling interval. Journal of the Operational Research Society, 2011, 62(1): 124-133
[21]
Panagiotidou S, Tagaras G. Statistical process control and condition-based maintenance: a meaningful relationship through data sharing. Production and Operations Management, 2010, 19(2): 156-171
[22]
Wu J M, Makis V. Economic and economic-statistical design of a chi-square chart for CBM. European Journal of Operational Research, 2008, 188(2): 516-529
[23]
Makis V. Multivariate Bayesian process control for a finite production run. European Journal of Operational Research, 2009, 194(3): 795-806
[24]
Wang W B. A simulation-based multivariate Bayesian control chart for real time condition-based maintenance of complex systems. European Journal of Operational Research, 2012, 218(3): 726-734
[25]
Liu L P, Yu M M, Ma Y Z, Tu Y L. Economic and economic-statistical designs of an X control chart for two-unit series systems with condition-based maintenance. European Journal of Operational Research, to be published
[26]
Van Noortwijk J M, Klatter H E. The use of lifetime distributions in bridge maintenance and replacement modelling. Computers and Structures, 2004, 82(13-14): 1091-1099
[27]
Kim S, Frangopol D M. Cost-based optimum scheduling of inspection and monitoring for fatigue-sensitive structures under uncertainty. Journal of Structural Engineering, 2011, 137(11): 1319-1331
[28]
Kaiser K A, Gebraeel N Z. Predictive maintenance management using sensor-based degradation models. IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, 2009, 39(4): 840-849
[29]
Gebraeel N Z, Lawley M A, Li R, Ryan J K. Residual-life distributions from component degradation signals: a Bayesian approach. IIE Transactions, 2005, 37(6): 543-557
[30]
Elwany A H, Gebraeel N Z, Maillart L M. Structured replacement policies for components with complex degradation processes and dedicated sensors. Operations Research, 2011, 59(3): 684-695
[31]
You M Y, Liu F, Wang W, Meng G. Statistically planned and individually improved predictive maintenance management for continuously monitored degrading systems. IEEE Transactions on Reliability, 2010, 59(4): 744-753
[32]
Fan Hong-Dong, Hu Chang-Hua, Chen Mao-Yin, Zhou Dong-Hua. A degradation measurement based decision support method for optimal predictive maintenance policy. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2009, 37(Sup.I): 45-48(樊红东, 胡昌华, 陈茂银, 周东华. 基于退化数据的最优预测维护决策支持方法. 华中科技大学学报(自然科学版), 2009, 37(Sup.I): 45-48)
[33]
Wei M H, Chen M Y, Zhou D H. Multi-sensor information based remaining useful life prediction with anticipated performance. IEEE Transactions on Reliability, 2013, 62(1): 183-198
[34]
Si X S, Wang W B, Chen M Y, Hu C H, Zhou D H. A degradation path-dependent approach for remaining useful life estimation with an exact and closed-form solution. European Journal of Operational Research, 2013, 226(1): 53-66
[35]
Sun J W, Li L, Xi L F. Modified two-stage degradation model for dynamic maintenance threshold calculation considering uncertainty. IEEE Transactions on Automation Science and Engineering, 2012, 9(1): 209-212
[36]
Wang W, Christer A H. Towards a general condition based maintenance model for a stochastic dynamic system. Journal of the Operational Research Society, 2000, 51(2): 145-155
[37]
Wang W. Overview of a semi-stochastic filtering approach for residual life estimation with applications in condition based maintenance. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2011, 225(2): 185-197
[38]
Deng Xin-Yang, Deng Yong, Zhang Ya-Juan, Liu Qi. A belief Markov model and its application. Acta Automatica Sinica, 2012, 38(4): 666-672(邓鑫洋, 邓勇, 章雅娟, 刘琪. 一种信度马尔科夫模型及应用. 自动化学报, 2012, 38(4): 666-672)
[39]
Kennedy W J, Wayne P J, Fredendall L D. An overview of recent literature on spare parts inventories. International Journal of Production Economics, 2002, 76(2): 201-215
[40]
Armstrong M J, Atkins D A. A note on joint optimization of maintenance and inventory. IIE Transactions, 1998, 30(2): 143-149
[41]
Zohrul Kabir A B M, Al-Olayan A S. Joint optimization of age replacement and continuous review spare provisioning policy. International Journal of Operations and Production Management, 1994, 14(7): 53-69
[42]
Rausch M, Liao H T. Joint production and spare part inventory control strategy driven by condition based maintenance. IEEE Transactions on Reliability, 2010, 59(3): 507-516
[43]
Xie J, Wang H W. Joint optimization of condition-based preventive maintenance and spare ordering policy. In: Proceedings of the 4th International Conference on Wireless Communications, Networking and Mobile Computing. Dalian, China: IEEE, 2008. 1-5
[44]
Louit D, Pascual R, Banjevic D, Jardine A K S. Condition-based spares ordering for critical components. Mechanical Systems and Signal Processing, 2011, 25(5): 1837-1848
[45]
Zhou Dong-Hua, Ye Yin-Zhong. Fault Diagnosis and Fault-Tolerant Control. Beijing: Tsinghua University Press, 2000(周东华, 叶银忠. 现代故障诊断与容错控制. 北京: 清华大学出版社, 2000)
[46]
Bevilacqua M, Braglia M. The analytic hierarchy process applied to maintenance strategy selection. Reliability Engineering and System Safety, 2000, 70(1): 71-83
[47]
Venkatasubramanian V, Rengaswamy R, Kavuri S N, Kewen Y. A review of process fault detection and diagnosis: Part III: Process history based methods. Computers and Chemical Engineering, 2003, 27(3): 327-346
[48]
Si X S, Wang W B, Hu C H, Zhou D H. Remaining useful life estimation——a review on the statistical data driven approaches. European Journal of Operational Research, 2011, 213(1): 1-14
[49]
Ahmad R, Kamaruddin S. An overview of time-based and condition-based maintenance in industrial application. Computers and Industrial Engineering, 2012, 63(1): 135-149
[50]
Heng A, Zhang S, Tan A C C, Mathew J. Rotating machinery prognostics: state of the art, challenges and opportunities. Mechanical Systems and Signal Processing, 2009, 23(3): 724-739
Fan Hong-Dong. Research on Maintenance Decision Modeling and Optimization Methods for Complex Repairable Systems [Ph.D. dissertation], High Technology Institute of Xi'an, China, 2012(樊红东. 复杂可修系统维修决策建模与优化方法研究 [博士学位论文], 第二炮兵工程大学, 中国, 2012)
[53]
Levy K, Vázquez-Abad F J. Change-point monitoring for online stochastic approximations. Automatica, 2010, 46(10): 1657-1674
[54]
Frisén M. Statistical surveillance. Optimality and methods. International Statistical Review, 2003, 71(2): 403-434
[55]
Si Xiao-Sheng, Hu Chang-Hua, Zhou Dong-Hua. Nonlinear degradation process modeling and remaining useful life estimation subject to measurement error. Acta Automatica Sinica, 2013, 39(5): 590-601 (司小胜, 胡昌华, 周东华. 带测量误差的非线性退化过程建模与剩余寿命估计. 自动化学报, 2013, 39(5): 590-601)
[56]
Bae S J, Kvam P H. A change-point analysis for modeling incomplete burn-in for light displays. IIE Transactions, 2006, 38(6): 489-498
[57]
Lin J. A two-stage failure model for Bayesian change point analysis. IEEE Transactions on Reliability, 2008, 57(2): 388-393
[58]
You M Y, Li L, Meng G, Ni J. Two-zone proportional hazard model for equipment remaining useful life prediction. Journal of Manufacturing Science and Engineering, 2010, 132(4): 041008(1-6)
[59]
Stoumbos Z G, Reynolds M R Jr, Ryan T P, Woodall W H. The state of statistical process control as we proceed into the 21st century. Journal of the American Statistical Association, 2000, 95(451): 992-998
[60]
Cassady C R, Bowden R O, Liew L, Pohl E A. Combining preventive maintenance and statistical process control: a preliminary investigation. IIE Transactions, 2000, 32(6): 471-478
[61]
Linderman K, McKone-Sweet K E, Anderson J C. An integrated systems approach to process control and maintenance. European Journal of Operational Research, 2005, 164(2): 324-340
[62]
Zhou W H, Zhu G L. Economic design of integrated model of control chart and maintenance management. Mathematical and Computer Modelling, 2008, 47(11-12): 1389-1395
[63]
Panagiotidou S, Nenes G. An economically designed, integrated quality and maintenance model using an adaptive Shewhart chart. Reliability Engineering and System Safety, 2009, 94(3): 732-741
[64]
Makis V. Multivariate bayesian control chart. Operations Research, 2008, 56(2): 487-496
[65]
Yin Z J, Makis V. Economic and economic-statistical design of a multivariate Bayesian control chart for condition-based maintenance. IMA Journal of Management Mathematics, 2011, 22(1): 47-63
[66]
Yang J N, Manning S D. Stochastic crack growth analysis methodologies for metallic structures. Engineering Fracture Mechanics, 1990, 37(5): 1105-1124
[67]
Biondini F, Bontempi F, Frangopo D M, Malerba P G. Probabilistic service life assessment and maintenance planning of concrete structures. Journal of Structural Engineering, 2006, 132(5): 810-825
[68]
Wang Jian. Research on maintenance scheduling for generating units in electricity market environment [Ph.D. dissertation], China Agricultural University, China, 2004(王健. 电力市场环境下发电机组检修计划的研究 [博士学位论文], 中国农业大学, 中国, 2004)
[69]
Si X S, Wang W B, Hu C H, Chen M Y, Zhou D H. A Wiener-process-based degradation model with a recursive filter algorithm for remaining useful life estimation. Mechanical Systems and Signal Processing, 2013, 35(1-2): 219-237
[70]
You M Y, Li L, Meng G, Ni J. Cost-effective updated sequential predictive maintenance policy for continuously monitored degrading systems. IEEE Transactions on Automation Science and Engineering, 2010, 7(2): 257-265
[71]
Si X S, Wang W H, Hu C H. A real-time variable cost-based maintenance model from prognostic information. In: Proceedings of 2012 IEEE Conference on Prognostics and System Health Management. Beijing, China: IEEE, 2012. 1-6
[72]
Si X S, Wang W B, Hu C H, Zhou D H, Pecht M G. Remaining useful life estimation based on a nonlinear diffusion degradation process. IEEE Transactions on Reliability, 2012, 61(1): 50-67
[73]
Li L, You M Y, Ni J. Reliability-based dynamic maintenance threshold for failure prevention of continuously monitored degrading systems. Journal of Manufacturing Science and Engineering, 2009, 131(3): 1010-1018
[74]
Arnaiz A, Ferreiro S, Buderath M. New decision support system based on operational risk assessment to improve aircraft operability. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2010, 224(3): 137-147
[75]
Hu You-Tao, Hu Chang-Hua, Kong Xiang-Yu, Zhou Zhi-Jie. Real-time lifetime prediction method based on wavelet support vector regression and fuzzy c-means clustering. Acta Automatica Sinica, 2012, 38(3): 331-340(胡友涛, 胡昌华, 孔祥玉, 周志杰. 基于WSVR和FCM聚类的实时寿命预测方法. 自动化学报, 2012, 38(3): 331-340)
[76]
Wang W B, Hussin B, Jefferis T. A case study of condition based maintenance modelling based upon the oil analysis data of marine diesel engines using stochastic filtering. International Journal of Production Economics, 2012, 136(1): 84-92
[77]
Carr M J, Wang W B. An approximate algorithm for prognostic modelling using condition monitoring information. European Journal of Operational Research, 2011, 211(1): 90-96
[78]
Ghasemi A, Yacout S, Ouali M S. Optimal condition based maintenance with imperfect information and the proportional hazards model. International Journal of Production Research, 2007, 45(4): 989-1012
[79]
Xiang Y S, Cassady C R, Pohl E A. Optimal maintenance policies for systems subject to a Markovian operating environment. Computers and Industrial Engineering, 2012, 62(1): 190-197
[80]
Van Noortwijk J M. A survey of the application of gamma processes in maintenance. Reliability Engineering and System Safety, 2009, 94(1): 2-21
[81]
Armstrong M J, Atkins D R. Joint optimization of maintenance and inventory policies for a simple system. IIE Transactions, 1996, 28(5): 415-424
[82]
Allen S G, D’Esopo D A. An ordering policy for repairable stock items. Operations Research, 1968, 16(3): 669-674
[83]
Van Horenbeek A, Buré J, Cattrysse D, Pintelon L, Vansteenwegen P. Joint maintenance and inventory optimization systems: a review. International Journal of Production Economics, 2013, 143(2): 499-508
[84]
Acharya D, Nagabhushanam G, Alam S S. Jointly optimal block-replacement and spare provisioning policy. IEEE Transactions on Reliability, 1986, 35(4): 447-451
[85]
Wang L, Chu J, Mao W J. A condition-based order-replacement policy for a single-unit system. Applied Mathematical Modelling, 2008, 32(11): 2274-2289
[86]
Jiang Yun-Peng, Chen Mao-Yin, Zhou Dong-Hua. Modeling of condition-based maintenance and spare parts provisioning policy for single-unit system with two-stage degradation. Journal of Nanjing University of Aeronautics and Astronautics, 2011, 43(S1): 147-151(蒋云鹏, 陈茂银, 周东华. 两阶段退化单部件系统的视情维护和备件供给策略建模. 南京航空航天大学学报, 2011, 43(S1): 147-151)
[87]
Wang L, Chu J, Mao W J. A condition-based replacement and spare provisioning policy for deteriorating systems with uncertain deterioration to failure. European Journal of Operational Research, 2009, 194(1): 184-205
[88]
Wang L, Chu J, Mao W J. An optimum condition-based replacement and spare provisioning policy based on Markov chains. Journal of Quality in Maintenance Engineering, 2008, 14(4): 387-401
[89]
Elwany A H, Gebraeel N Z. Sensor-driven prognostic models for equipment replacement and spare parts inventory. IIE Transactions, 2008, 40(7): 629-639
