• Title of article

    An overview of reinforcement learning and deep reinforcement learning for conditionbased maintenance

  • Author/Authors

    Dehghani Ghobadi, Zahra School of Mathematics, Statistics and Computer Science - College of Science - University of Tehran, Tehran, Iran , Haghighi, Firoozeh School of Mathematics, Statistics and Computer Science - College of Science - University of Tehran, Tehran, Iran , Safari, Abdollah School of Mathematics, Statistics and Computer Science - College of Science - University of Tehran, Tehran, Iran

  • Pages
    9
  • From page
    81
  • To page
    89
  • Abstract
    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.
  • Keywords
    Condition-based maintenance , Deep reinforcement learning , Markov decision process
  • Journal title
    International Journal of Reliability, Risk and Safety: Theory and Application
  • Serial Year
    2021
  • Record number

    2734646