Optimization of System Availability for a Multi-State Preventive Maintenance Model from the Perspective of a System’s Components
RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 4, pp. 773-794.

This study aims at the multi-state degraded system with multi-state components to propose a novel approach of performance evaluation and a preventive maintenance model from the perspective of a system’s components. The general non-homogeneous continuous-time Markov model (NHCTMM) and its analogous Markov reward model (NHCTMRM) are used to quantify the intensity of state transitions during the degradation process. Accordingly, the bound approximation approach is applied to solve the established NHCTMMs and NHCTMRMs, thus evaluating system performance including system availability and total maintenance cost to overcome their inherent computational difficulties. Furthermore, this study adopts a genetic algorithm (GA) to optimize a proposed preventive maintenance model. A simulation illustrates the feasibility and practicability of the proposed approach.

Reçu le :
Accepté le :
DOI : 10.1051/ro/2015004
Classification : 60Jxx, 90B25
Mots clés : Multi-state components, preventive maintenance, non-homogeneous continuous-time Markov models, genetic algorithm, bound approximation approach
Wang, Chun-Ho 1 ; Huang, Chao-Hui 2

1 Department of Power Vehicle and Systems Engineering, Chung Cheng Institute of Technology, National Defense University No.75, Shiyuan Rd., Daxi Township, Tauyuan County 33551, Taiwan (R.O.C.)
2 Department of Applied Science, R.O.C. Naval Academy No.669, Junxiao Rd., Zuoying District, Kaohsiung City 81345, Taiwan (R.O.C.).
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     title = {Optimization of {System} {Availability} for a {Multi-State} {Preventive} {Maintenance} {Model} from the {Perspective} of a {System{\textquoteright}s} {Components}},
     journal = {RAIRO - Operations Research - Recherche Op\'erationnelle},
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Wang, Chun-Ho; Huang, Chao-Hui. Optimization of System Availability for a Multi-State Preventive Maintenance Model from the Perspective of a System’s Components. RAIRO - Operations Research - Recherche Opérationnelle, Tome 49 (2015) no. 4, pp. 773-794. doi : 10.1051/ro/2015004. http://www.numdam.org/articles/10.1051/ro/2015004/

A. Arab, N Ismail and Ls. Lee Maintenance scheduling incorporating dynamics of production system and real-time information from workstations. J. Intell. Manuf. 24 (2013) 695–705. | DOI

D. Chen and K.S. Trivedi, Closed-form analytical results for condition-based maintenance. Reliab. Eng. Syst. Safe. 76 (2002) 43–51. | DOI

Y. Ding, A. Lisnianski, I. Frenkel and L. Khvatskin, Optimal corrective maintenance contract planning for aging multi-state system. Appl. Stoch. Model. Bus. 25 (2009) 612–631. | DOI | Zbl

P. Dovan and C. Berenguer, Condition-Based Maintenance with Imperfect Preventive Repairs for a Deteriorating Production System. Qual. Relial. Eng. Int. 28 (2012) 624–633. | DOI

R. Howard, Dynamic programming and Markov process. Cambridge, MIT Press MA (1960). | Zbl

C.H. Huang and C.H. Wang Optimization of preventive maintenance for a multi-state degraded system by monitoring component performance. J. Intell. Manuf. Doi: (2014). | DOI

C.C. Huang and J. Yuan, A two-stage preventive maintenance policy for a multi-state deterioration system. Reliab. Eng. Syst. Safe. 95 (2010) 1255–1260. | DOI

A. Khatab, D. Ait-Kadi and N. Rezg, A condition-based maintenance model for availability optimization for stochastic degrading systems. In Proc. of 9th International Conf. Model., Optim. Simul. (MOSIM’ 12) (2012).

G. Levitin, Universal generating function in reliability analysis and optimization. Springer, London (2005).

G. Levitin and A. Lisnianski, Optimization of imperfect preventive maintenance for multi-state systems. Reliab. Eng. Syst. Safe. 67 (2000) 193–203. | DOI

A. Lisnianski, Extended block diagram method for a multi-state system reliability assessment. Reliab. Eng. Syst. Safe. 92 (2007) 1601–1607. | DOI

A. Lisnianski and G. Levitin, Multi-state system reliability: assessment, optimization and applications. World Scientific, Singapore (2003). | Zbl

A. Lisnianski, I. Frenkel, L. Khvatskin and Y. Ding, Maintenance contract assessment for aging systems. Qual. Relial. Eng. Int. 24 (2008) 519–531. | DOI

A. Lisnianski I. Frenkel and Y. Ding, Multi-state system reliability analysis and optimiza-tion for engineers and industrial managers. Springer, London (2010). | Zbl

Y. Liu and H.Z. Huang, Optimal replacement policy for multi-state system under imperfect maintenance. IEEE Trans. Reliab. 59 (2010) 483–495. | DOI

Y. Liu and K.C. Kapur, Customer’s cumulative experience measures for reliability of non-repairable aging multi-state systems. Qual. Tech. Quant. Manage. 4 (2007) 225–234. | DOI

Y. Liu and K.C. Kapur, New model and measurement for reliability of multi-state systems. Springer, London (2008).

H. Mine and S. Osaki, Markovian decision processes. Elsevier. New York (1970). | Zbl

S. Nagayama T. Sasao and J.T. Butler, In Proc. Analysis of multi-state systems with multi-state components using EVMDDs. In Proc. Multiple-Valued Logic (ISMVL), 42nd international Symposium on IEEE (2012) 122–127.

N. Nahas, A. Khatab, D. Ait-Kadi and M. Nourelfath, Extended great deluge algorithm for the imperfect preventive maintenance optimization of multi-state systems. Reliab. Eng. Syst. Safe. 93 (2008) 1658–1672. | DOI

A. Platis, A generalized formulation for the performability indicator. Int. J. Comput. Math. Appl. 51 (2006) 239–246. | DOI | Zbl

A. Platis, N. Limnios and M. Ledu, Dependability Analysis of Systems Modeled by Non- Homogenous Markov Chains. Reliab. Eng. Syst. Safe. 61 (1998) 235–249. | DOI

C.M. Tan and N. Raghavan, A framework to practical predictive maintenance modeling for multi-state systems. Reliab. Eng. Syst. Safe. 93 (2008) 1138–1150. | DOI

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