Self-repair of smart manufacturing systems by deep reinforcement learning

Bogdan I Epureanu, Xingyu Li*, Aydin Nassehi, Yoram Koren

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

29 Downloads (Pure)


Smart manufacturing is built on complex decision-making in real-time based on data from networked machines and sensors. As a potential enabler of smart manufacturing, reconfigurability enhances adaptability to demands and enriches the utility of the collected data. This study focuses on a synergistic combination of advanced manufacturing technologies in a highly diverse market environment, to identify deficient components by inferring from changes in product quality and to sustain the operation of the manufacturing system by creating multiple-level self-repair strategies. Deep reinforcement learning is then used to select the strategy based on system status and performance.
Original languageEnglish
JournalCIRP Annals - Manufacturing Technology
Early online date18 May 2020
Publication statusE-pub ahead of print - 18 May 2020


  • reconfiguration
  • decision making
  • artificial intelligence


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