Condition-based maintenance (CBM) involves making decisions on maintenance based on the actual deterioration conditions of the components. It consists of a chain of states representing various stages of deterioration and a set of maintenance actions. Therefore, condition-based maintenance is a sequential decision-making problem. Reinforcement Learning(RL) is a subfield of Machine Learning proposed for automated decision-making. This article provides an overview of reinforcement learning and deep reinforcement learning methods that have been used so far in condition-based maintenance optimization.
Dehghani Ghobadi, Z., Haghighi, F., & safari, A. (2021). An overview of reinforcement learning and deep reinforcement learning for condition-based maintenance. International Journal of Reliability, Risk and Safety: Theory and Application, 4(2), 81-89. doi: 10.30699/IJRRS.4.2.9
MLA
Zahra Dehghani Ghobadi; Firoozeh Haghighi; Abdollah safari. "An overview of reinforcement learning and deep reinforcement learning for condition-based maintenance". International Journal of Reliability, Risk and Safety: Theory and Application, 4, 2, 2021, 81-89. doi: 10.30699/IJRRS.4.2.9
HARVARD
Dehghani Ghobadi, Z., Haghighi, F., safari, A. (2021). 'An overview of reinforcement learning and deep reinforcement learning for condition-based maintenance', International Journal of Reliability, Risk and Safety: Theory and Application, 4(2), pp. 81-89. doi: 10.30699/IJRRS.4.2.9
VANCOUVER
Dehghani Ghobadi, Z., Haghighi, F., safari, A. An overview of reinforcement learning and deep reinforcement learning for condition-based maintenance. International Journal of Reliability, Risk and Safety: Theory and Application, 2021; 4(2): 81-89. doi: 10.30699/IJRRS.4.2.9
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