Reinforcement Learning based on Stochastic Dynamic Programming for Condition-based Maintenance of Deteriorating Production Processes

Rasay, Hasan; Naderkhani, Farnoosh; Golmohammadi, Amir Mohammad

doi:10.1109/icphm53196.2022.9815668

Cited by 6 publications

(3 citation statements)

References 13 publications

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“…k2L u k P r, k ; for r 2 L, u 0 = 0: (11) In the following, different terms of this linear equations are computed.…”

Section: Development Of Pomdpmentioning

confidence: 99%

“…The optimal policy is characterized to minimize the long-term average cost per time unit. Rasay et al 11 provides an POMDP for maintenance planning of a deteriorating system with different operational states and a failure state. It is assumed that data about the quality of produced items provide incomplete information regarding the system state.…”

Section: Introductionmentioning

confidence: 99%

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Optimal condition based maintenance using attribute Bayesian control chart

Rasay

Hadian

Naderkhani

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part O:

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Condition-based maintenance (CBM) has been emerged as a relatively new trend in maintenance management. Instead of conducting preventive maintenance actions in specified time intervals, the CBM program collects information through condition monitoring, then recommends maintenance actions based on the observed data. On the other hand, Bayesian control charts use the posterior probability of being the system in an unhealthy state as the chart statistic. An attribute Bayesian control chart is employed in this study to monitor a deteriorating system and plan CBM actions based on a continuous-time homogeneous Markov chain. The system consists of three states: healthy, unhealthy, and failure states. A partially observable Markov decision process (POMDP) is developed, which optimally determines the sample size, sampling interval, and warning limit to minimize the long-term expected cost per time unit. Numerical examples and sensitivity analyses are conducted to clarify the performance of the proposed attribute control chart. To the best of the authors’ knowledge, this is the first study of the applications of attribute Bayesian control charts in condition-based maintenance.

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“…k2L u k P r, k ; for r 2 L, u 0 = 0: (11) In the following, different terms of this linear equations are computed.…”

Section: Development Of Pomdpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal condition based maintenance using attribute Bayesian control chart

Rasay

Hadian

Naderkhani

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part O:

View full text Add to dashboard Cite

show abstract

“…The focus of the research in this area has been on proposing metaheuristic methods and competitive algorithms like evolution strategies and ANNs, grouping evolution strategies, particle swarm optimization, honey bee optimization, genetic algorithms, beam search algorithm, differential evolution approach, ant colony algorithm, and local search algorithm, in the recent decade [ 10 , [22] , [23] , [24] , [25] , [26] , [27] , [28] , [29] , [30] , [31] ]. In addition to the mentioned literature, several exact methods like the branch & bound [ 32 ], linear programming [ 33 ], dynamic programming [ 34 ], integer programming [ 35 ], and mixed-integer programming [ 36 ], were proposed to solve different types of ALBPs. Recently, Fleszar [ 37 ] developed a mixed-integer linear programming (MILP) model for two different ALBPs.…”

Section: Introductionmentioning

confidence: 99%