A review of condition-based maintenance: Its prognostic and operational aspects

Abstract

Condition-based maintenance (CBM) detects early signs of failure and dictates when maintenance should be performed based on the actual condition of a system. In this paper, we first review some of the recent research on CBM under various physical structures and signal data. Then, we summarize several kinds of prognostic models that use monitoring information to estimate the reliability of complex systems or products. Monitoring information also facilitates operational decisions in production planning, spare parts management, reliability improvement, and prognostics and health management. Finally, we suggest some research opportunities for the reliability and operations management communities to fill the research gap between these two fields.

Keywords

condition-based maintenance / prognostics / operational decision-making / reliability

References

[1] Aizpurua J I, Catterson V M, Papadopoulos Y, Chiacchio F, D’Urso D (2017). Supporting group maintenance through prognostics-enhanced dynamic dependability prediction. Reliability Engineering & System Safety, 168: 171–188

[2] Alaswad S, Xiang Y (2017). A review on condition-based maintenance optimization models for stochastically deteriorating system. Reliability Engineering & System Safety, 157: 54–63

[3] Armstrong M J, Atkins D R (1996). Joint optimization of maintenance and inventory policies for a simple system. IIE Transactions, 28(5): 415–424

[4] Aronis K P, Magou I, Dekker R, Tagaras G (2004). Inventory control of spare parts using a Bayesian approach: A case study. European Journal of Operational Research, 154(3): 730–739

[5] Attardi L, Guida M, Pulcini G (2005). A mixed-Weibull regression model for the analysis of automotive warranty data. Reliability Engineering & System Safety, 87(2): 265–273

[6] Bae S J, Mun B M, Chang W, Vidakovic B (2019). Condition monitoring of a steam turbine generator using wavelet spectrum based control chart. Reliability Engineering & System Safety, 184: 13–20

[7] Bahria N, Chelbi A, Bouchriha H, Dridi I H (2019). Integrated production, statistical process control, and maintenance policy for unreliable manufacturing systems. International Journal of Production Research, 57(8): 2548–2570

[8] Batun S, Maillart L M (2012). Reassessing tradeoffs inherent to simultaneous maintenance and production planning. Production and Operations Management, 21(2): 396–403

[9] Berrade M D, Scarf P A, Cavalcante C A (2018). Conditional inspection and maintenance of a system with two interacting components. European Journal of Operational Research, 268(2): 533–544

[10] Byon E, Ding Y (2010). Season-dependent condition-based maintenance for a wind turbine using a partially observed Markov decision process. IEEE Transactions on Power Systems, 25(4): 1823–1834

[11] Chehade A, Bonk S, Liu K (2017). Sensory-based failure threshold estimation for remaining useful life prediction. IEEE Transactions on Reliability, 66(3): 939–949

[12] Cheng G Q, Zhou B H, Li L (2018). Integrated production, quality control and condition-based maintenance for imperfect production systems. Reliability Engineering & System Safety, 175: 251–264

[13] Cinlar E, Bazant Z P, Osman E M (1977). Stochastic process for extrapolating concrete creep. ACSE Journal of the Engineering Mechanics Division, 103(6): 1069–1088

[14] Cipollini F, Oneto L, Coraddu A, Murphy A J, Anguita D (2018). Condition-based maintenance of naval propulsion systems: Data analysis with minimal feedback. Reliability Engineering & System Safety, 177: 12–23

[15] de Jonge B (2019). Discretizing continuous-time continuous-state deterioration processes, with an application to condition-based maintenance optimization. Reliability Engineering & System Safety, 188: 1–5

[16] de Jonge B, Scarf P A (2020). A review on maintenance optimization. European Journal of Operational Research, 285(3): 805–824

[17] Do P, Assaf R, Scarf P, Iung B (2019). Modelling and application of condition-based maintenance for a two-component system with stochastic and economic dependencies. Reliability Engineering & System Safety, 182: 86–97

[18] Ellingwood B R, Mori Y (1993). Probabilistic methods for condition assessment and life prediction of concrete structure in nuclear power plants. Nuclear Engineering and Design, 142(2–3): 155–166

[19] Elwany A H, Gebraeel N Z (2008). Sensor-driven prognostic models for equipment replacement and spare parts inventory. IIE Transactions, 40(7): 629–639

[20] Feng Q, Bi X, Zhao X, Chen Y, Sun B (2017). Heuristic hybrid game approach for fleet condition-based maintenance planning. Reliability Engineering & System Safety, 157: 166–176

[21] Fitouhi M C, Nourelfath M, Gershwin S B (2017). Performance evaluation of a two-machine line with a finite buffer and condition-based maintenance. Reliability Engineering & System Safety, 166: 61–72

[22] Ghamlouch H, Fouladirad M, Grall A (2017). The use of real option in condition-based maintenance scheduling for wind turbines with production and deterioration uncertainties. Reliability Engineering & System Safety, 188: 614–623

[23] Gössinger R, Helmke H, Kaluzny M (2017). Condition-based release of maintenance jobs in a decentralised production-maintenance system—An analysis of alternative stochastic approaches. International Journal of Production Economics, 193: 528–537

[24] Hanachi H, Mechefske C, Liu J, Banerjee A, Chen Y (2018). Performance-based gas turbine health monitoring, diagnostics, and prognostics: A survey. IEEE Transactions on Reliability, 67(3): 1340–1363

[25] Harris F W (1990). How many parts to make at once. Operations Research, 38(6): 947–950

[26] He Y, Gu C, Chen Z, Han X (2017). Integrated predictive maintenance strategy for manufacturing systems by combining quality control and mission reliability analysis. International Journal of Production Research, 55(19): 5841–5862

[27] Huang Y S, Huang C D, Ho J W (2017). A customized two-dimensional extended warranty with preventive maintenance. European Journal of Operational Research, 257(3): 971–978

[28] Huynh K T (2020). Modeling past-dependent partial repairs for condition-based maintenance of continuously deteriorating systems. European Journal of Operational Research, 280(1): 152–163

[29] Huynh K T, Grall A, Bérenguer C (2017). Assessment of diagnostic and prognostic condition indices for efficient and robust maintenance decision-making of systems subject to stress corrosion cracking. Reliability Engineering & System Safety, 159: 237–254

[30] Jafari L, Makis V (2015). Joint optimal lot sizing and preventive maintenance policy for a production facility subject to condition monitoring. International Journal of Production Economics, 169: 156–168

[31] Jafari L, Makis V (2016). Optimal lot-sizing and maintenance policy for a partially observable production system. Computers & Industrial Engineering, 93: 88–98

[32] Jafari L, Makis V (2019). Optimal production and maintenance policy for a partially observable production system with stochastic demand. International Journal of Industrial and Systems Engineering, 13(7): 449–456

[33] Jahani S, Kontar R, Zhou S Y, Veeramani D (2020). Remaining useful life prediction based on degradation signals using monotonic B-splines with infinite support. IISE Transactions, 52(5): 537–554

[34] Kazaz B, Sloan T W (2008). Production policies under deteriorating process conditions. IIE Transactions, 40(3): 187–205

[35] Khatab A, Diallo C, Aghezzaf E H, Venkatadri U (2019). Integrated production quality and condition-based maintenance optimisation for a stochastically deteriorating manufacturing system. International Journal of Production Research, 57(8): 2480–2497

[36] Kian R, Bektaş T, Ouelhadj D (2019). Optimal spare parts management for vessel maintenance scheduling. Annals of Operations Research, 272(1–2): 323–353

[37] Kim H, Kim J T, Heo G (2018). Failure rate updates using condition-based prognostics in probabilistic safety assessments. Reliability Engineering & System Safety, 175: 225–233

[38] Kim M, Song C, Liu K (2019). A generic health index approach for multisensor degradation modeling and sensor selection. IEEE Transactions on Automation Science and Engineering, 16(3): 1426–1437

[39] Kim M J, Makis V (2013). Joint optimization of sampling and control of partially observable failing systems. Operations Research, 61(3): 777–790

[40] Kontar R, Zhou S, Sankavaram C, Du X, Zhang Y (2018). Nonparametric-condition-based remaining useful life prediction incorporating external factors. IEEE Transactions on Reliability, 67(1): 41–52

[41] Kurt M, Kharoufeh J P (2010). Monotone optimal replacement policies for a Markovian deteriorating system in a controllable environment. Operations Research Letters, 38(4): 273–279

[42] Lam J Y J, Banjevic D (2015). A myopic policy for optimal inspection scheduling for condition based maintenance. Reliability Engineering & System Safety, 144: 1–11

[43] Lee J, Wu F, Zhao W, Ghaffari M, Liao L, Siegel D (2014). Prognostics and health management design for rotary machinery systems— Reviews, methodology and applications. Mechanical Systems and Signal Processing, 42(1–2): 314–334

[44] Lee M L T, Whitmore G A (2006). Threshold regression for survival analysis: Modeling event times by a stochastic process reaching a boundary. Statistical Science, 21(4): 501–513

[45] Levitin G, Xing L, Dai Y (2017). Preventive replacements in real-time standby systems with periodic backups. IEEE Transactions on Reliability, 66(3): 771–782

[46] Li R, Ryan J K (2011). A Bayesian inventory model using real-time condition monitoring information. Production and Operations Management, 20(5): 754–771

[47] Li Y, Chang Q, Biller S, Xiao G (2014). Event-based modelling of distributed sensor networks in battery manufacturing. International Journal of Production Research, 52(14): 4239–4252

[48] Li Y, Tang Q, Chang Q, Brundage M P (2017). An event-based analysis of condition-based maintenance decision-making in multistage production systems. International Journal of Production Research, 55(16): 4753–4764

[49] Lin L, Luo B, Zhong S S (2018). Multi-objective decision-making model based on CBM for an aircraft fleet with reliability constraint. International Journal of Production Research, 56(14): 4831–4848

[50] Lin X, Basten R J I, Kranenburg A A, van Houtum G J (2017). Condition based spare parts supply. Reliability Engineering & System Safety, 168: 240–248

[51] Liu B, Liang Z, Parlikad A K, Xie M, Kuo W (2017a). Condition-based maintenance for systems with aging and cumulative damage based on proportional hazards model. Reliability Engineering & System Safety, 168: 200–209

[52] Liu B, Wu S, Xie M, Kuo W (2017b). A condition-based maintenance policy for degrading systems with age- and state-dependent operating cost. European Journal of Operational Research, 263(3): 879–887

[53] Liu Q M, Dong M, Lv W Y, Ye C M (2019). Manufacturing system maintenance based on dynamic programming model with prognostics information. Journal of Intelligent Manufacturing, 30(3): 1155–1173

[54] Liu X, Li J, Al-Khalifa K N, Hamouda A S, Coit D W, Elsayed E A (2013). Condition-based maintenance for continuously monitored degrading systems with multiple failure modes. IIE Transactions, 45(4): 422–435

[55] Louit D, Pascual R, Banjevic D, Jardine A K (2011). Condition-based spares ordering for critical components. Mechanical Systems and Signal Processing, 25(5): 1837–1848

[56] Ma X Y, Liu B, Yang L, Peng R, Zhang X D (2020). Reliability analysis and condition-based maintenance optimization for a warm standby cooling system. Reliability Engineering & System Safety, 193: 106588

[57] Makis V, Jiang X (2003). Optimal replacement under partial observations. Mathematics of Operations Research, 28(2): 382–394

[58] Olde Keizer M C A, Flapper S D P, Teunter R H (2017a). Condition-based maintenance policies for systems with multiple dependent components: A review. European Journal of Operational Research, 261(2): 405–420

[59] Olde Keizer M C A, Teunter R H, Veldman J (2017b). Joint condition-based maintenance and inventory optimization for systems with multiple components. European Journal of Operational Research, 257(1): 209–222

[60] Olde Keizer M C A, Teunter R H, Veldman J, Babai M Z (2018). Condition-based maintenance for systems with economic dependence and load sharing. International Journal of Production Economics, 195: 319–327

[61] Peng C Y, Tseng S T (2009). Mis-specification analysis of linear degradation models. IEEE Transactions on Reliability, 58(3): 444–455

[62] Peng H, van Houtum G J (2016). Joint optimization of condition-based maintenance and production lot-sizing. European Journal of Operational Research, 253(1): 94–107

[63] Poppe J, Boute R N, Lambrecht M R (2018). A hybrid condition-based maintenance policy for continuously monitored components with two degradation thresholds. European Journal of Operational Research, 268(2): 515–532

[64] Shi H, Zeng J (2016). Real-time prediction of remaining useful life and preventive opportunistic maintenance strategy for multi-component systems considering stochastic dependence. Computers & Industrial Engineering, 93(3): 192–204

[65] Si X, Li T, Zhang Q, Hu X (2018). An optimal condition-based replacement method for systems with observed degradation signals. IEEE Transactions on Reliability, 67(3): 1281–1293

[66] Si X S, Wang W, Hu C H, Zhou D H (2011). Remaining useful life estimation—A review on the statistical data driven approaches. European Journal of Operational Research, 213(1): 1–14

[67] Skordilis E, Moghaddass R (2017). A condition monitoring approach for real-time monitoring of degrading systems using Kalman filter and logistic regression. International Journal of Production Research, 55(19): 5579–5596

[68] Sloan T W, Shanthikumar J G (2000). Combined production and maintenance scheduling for a multiple-product, single-machine production system. Production and Operations Management, 9(4): 379–399

[69] Song C, Liu K (2018). Statistical degradation modeling and prognostics of multiple sensor signals via data fusion: A composite health index approach. IISE Transactions, 50(10): 853–867

[70] Song C, Liu K, Zhang X (2019). A generic framework for multisensor degradation modeling based on supervised classification and failure surface. IISE Transactions, 51(11): 1288–1302

[71] Tang S, Guo X, Zhou Z (2014). Mis-specification analysis of linear Wiener process-based degradation models for the remaining useful life estimation. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 228(5): 478–487

[72] Topan E, Tan T, van Houtum G J, Dekker R (2018). Using imperfect advance demand information in lost-sales inventory systems with the option of returning inventory. IISE Transactions, 50(3): 246–264

[73] uit het Broek M A J, Teunter R H, de Jonge B, Veldman J, van Foreest N D (2019). Condition-based production planning: Adjusting production rates to balance output and failure risk. Manufacturing & Service Operations Management. In press, doi: 10.1287/msom.2019.0773

[74] Verbert K, de Schutter B, Babuška R (2018). A multiple-model reliability prediction approach for condition-based maintenance. IEEE Transactions on Reliability, 67(3): 1364–1376

[75] Vogl G W, Weiss B A, Helu M (2016). A review of diagnostic and prognostic capabilities and best practices for manufacturing. Journal of Intelligent Manufacturing, 30(1): 79–95

[76] Walter G, Flapper S D (2017). Condition-based maintenance for complex systems based on current component status and Bayesian updating of component reliability. Reliability Engineering & System Safety, 168: 227–239

[77] Wan Q, Liu C, Wu Y, Zhou W (2018). A TBE control chart-based maintenance policy for a service facility. Computers & Industrial Engineering, 126: 136–148

[78] Wang H K, Huang H Z, Li Y F, Yang Y J (2016). Condition-based maintenance with scheduling threshold and maintenance threshold. IEEE Transactions on Reliability, 65(2): 513–524

[79] Wang L, Lu Z Q, Ren Y F (2019). A rolling horizon approach for production planning and condition-based maintenance under uncertain demand. Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 233(6): 1014–1028

[80] Wang W (2007). A two-stage prognosis model in condition based maintenance. European Journal of Operational Research, 182(3): 1177–1187

[81] Wang W, Christer A H (2000). Towards a general condition based maintenance model for a stochastic dynamic system. Journal of the Operational Research Society, 51(2): 145–155

[82] Wang X, Xu D (2010). An inverse Gaussian process model for degradation data. Technometrics, 52(2): 188–197

[83] Wei G, Zhao X, He S, He Z (2019). Reliability modeling with condition-based maintenance for binary-state deteriorating systems considering zoned shock effects. Computers & Industrial Engineering, 130: 282–297

[84] Wu J, Deng C, Shao X Y, Xie S Q (2009). A reliability assessment method based on support vector machines for CNC equipment. Science in China Series E: Technological Sciences, 52(7): 1849–1857

[85] Wu S (2014). Construction of asymmetric copulas and its application in two-dimensional reliability modelling. European Journal of Operational Research, 238(2): 476–485

[86] Xu W, Wang W (2013). RUL estimation using an adaptive inverse Gaussian model. Chemical Engineering Transactions, 33: 331–336

[87] Yahyatabar A, Najafi A A (2018). Condition based maintenance policy for series-parallel systems through proportional hazards model: A multi-stage stochastic programming approach. Computers & Industrial Engineering, 126: 30–46

[88] Yan T, Lei Y G, Wang B, Han T Y, Si X S, Li N P (2020). Joint maintenance and spare parts inventory optimization for multi-unit systems considering imperfect maintenance actions. Reliability Engineering & System Safety, 202: 106994

[89] Ye Z S, Chen N (2014). The inverse Gaussian process as a degradation model. Technometrics, 56(3): 302–311

[90] Ye Z S, Murthy D N P (2016). Warranty menu design for a two-dimensional warranty. Reliability Engineering & System Safety, 155: 21–29

[91] Zhang J X, Hu C H, He X, Si X S, Liu Y, Zhou D H (2017). Lifetime prognostics for deteriorating systems with time-varying random jumps. Reliability Engineering & System Safety, 167: 338–350

[92] Zhang M, Revie M (2017). Continuous-observation partially observable semi-Markov decision processes for machine maintenance. IEEE Transactions on Reliability, 66(1): 202–218

[93] Zhang N, Fouladirad M, Barros A, Zhang J (2020). Condition-based maintenance for a k-out-of-n, deteriorating system under periodic inspection with failure dependence. European Journal of Operational Research, 287(1): 159–167

[94] Zhang X, Zeng J (2017). Joint optimization of condition-based opportunistic maintenance and spare parts provisioning policy in multiunit systems. European Journal of Operational Research, 262(2): 479–498

[95] Zhang Z, Si X, Hu C, Lei Y (2018). Degradation data analysis and remaining useful life estimation: A review on Wiener-process-based methods. European Journal of Operational Research, 271(3): 775–796

[96] Zhao S, Makis V, Chen S, Li Y (2018a). Evaluation of reliability function and mean residual life for degrading systems subject to condition monitoring and random failure. IEEE Transactions on Reliability, 67(1): 13–25

[97] Zhao X, He S, He Z, Xie M (2018b). Optimal condition-based maintenance policy with delay for systems subject to competing failures under continuous monitoring. Computers & Industrial Engineering, 124: 535–544

[98] Zhou X, Xi L, Lee J (2007). Reliability-centered predictive maintenance scheduling for a continuously monitored system subject to degradation. Reliability Engineering & System Safety, 92(4): 530–534

[99] Zhou Z J, Hu C H, Xu D L, Chen M Y, Zhou D H (2010). A model for real-time failure prognosis based on hidden Markov model and belief rule base. European Journal of Operational Research, 207(1): 269–283

[100] Zhu S, van Jaarsveld W, Dekker R (2020). Spare parts inventory control based on maintenance planning. Reliability Engineering & System Safety, 193: 106600

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