publication . Article . 2021

Towards online reinforced learning of assembly sequence planning with interactive guidance systems for industry 4.0 adaptive manufacturing

de Giorgio, Andrea; Maffei, Antonio; Onori, Mauro; Wang, Lihui;
Open Access English
  • Published: 11 May 2021
  • Publisher: KTH, Industriell produktion
  • Country: Sweden
Abstract
Literature shows that reinforcement learning (RL) and the well-known optimization algorithms derived from it have been applied to assembly sequence planning (ASP); however, the way this is done, as an offline process, ends up generating optimization methods that are not exploiting the full potential of RL. Today’s assembly lines need to be adaptive to changes, resilient to errors and attentive to the operators’ skills and needs. If all of these aspects need to evolve towards a new paradigm, called Industry 4.0, the way RL is applied to ASP needs to change as well: the RL phase has to be part of the assembly execution phase and be optimized with time and several ...
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free text keywords: Production Engineering, Human Work Science and Ergonomics, Produktionsteknik, arbetsvetenskap och ergonomi
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