Search algorithm of the assembly sequence of products by using past learning results

Keijiro Watanabe, Shuhei Inada

研究成果: Article査読

12 被引用数 (Scopus)

抄録

In the future smart factory, the production system will further head in the direction of on-demand production. Products will be assembled one by one based on different specifications of customers. In these recognitions, this paper considers a method for raising productivity of the robot work cell. Under the assumption that the dual-arm robot assembles products in the work cell where one robot is in charge of all steps of assembling the product, we propose a computational algorithm for searching the efficient assembly sequence and work assignment to the robot hands utilizing reinforcement learning. Furthermore, we intend to use past learning results to determine work plans of robots more effectively. The proposed methods can eliminate or decrease the workload of the robot teaching. In addition, they can contribute to shorten the assembly time of products by giving the efficient work plan. In this research, the basic theory for automating the work planning of actual assembled products is considered using a building block model.

本文言語English
論文番号107615
ジャーナルInternational Journal of Production Economics
226
DOI
出版ステータスPublished - 2020 8月

ASJC Scopus subject areas

  • ビジネス、管理および会計(全般)
  • 経済学、計量経済学
  • 経営科学およびオペレーションズ リサーチ
  • 産業および生産工学

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