Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry

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  • Additional Information
    • Publication Information:
      Hindawi Limited, 2019.
    • Publication Date:
      2019
    • Collection:
      LCC:Engineering (General). Civil engineering (General)
      LCC:Mathematics
    • Abstract:
      In semiconductor back-end production, the die attach process is one of the most critical steps affecting overall productivity. Optimization of this process can be modeled as a pick-and-place problem known to be NP-hard. Typical approaches are rule-based and metaheuristic methods. The two have high or low generalization ability, low or high performance, and short or long search time, respectively. The motivation of this paper is to develop a novel method involving only the strengths of these methods, i.e., high generalization ability and performance and short search time. We develop an interactive Q-learning in which two agents, a pick agent and a place agent, are trained and find a pick-and-place (PAP) path interactively. From experiments, we verified that the proposed approach finds a shorter path than the genetic algorithm given in previous research.
    • File Description:
      electronic resource
    • ISSN:
      1024-123X
      1563-5147
    • Relation:
      https://doaj.org/toc/1024-123X; https://doaj.org/toc/1563-5147
    • Accession Number:
      10.1155/2019/4602052
    • Rights:
      Journal Licence: CC BY
    • Accession Number:
      edsdoj.fc0569dea084dc9b10ba8b9d03e99c9
  • Citations
    • ABNT:
      GILSEUNG AHN et al. Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry. Mathematical Problems in Engineering, [s. l.], 2019. Disponível em: . Acesso em: 23 out. 2019.
    • AMA:
      Gilseung Ahn, Myunghwan Park, You-Jin Park, Sun Hur. Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry. Mathematical Problems in Engineering. 2019. doi:10.1155/2019/4602052.
    • APA:
      Gilseung Ahn, Myunghwan Park, You-Jin Park, & Sun Hur. (2019). Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry. Mathematical Problems in Engineering. https://doi.org/10.1155/2019/4602052
    • Chicago/Turabian: Author-Date:
      Gilseung Ahn, Myunghwan Park, You-Jin Park, and Sun Hur. 2019. “Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry.” Mathematical Problems in Engineering. doi:10.1155/2019/4602052.
    • Harvard:
      Gilseung Ahn et al. (2019) ‘Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry’, Mathematical Problems in Engineering. doi: 10.1155/2019/4602052.
    • Harvard: Australian:
      Gilseung Ahn, Myunghwan Park, You-Jin Park & Sun Hur 2019, ‘Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry’, Mathematical Problems in Engineering, viewed 23 October 2019, .
    • MLA:
      Gilseung Ahn, et al. “Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry.” Mathematical Problems in Engineering, 2019. EBSCOhost, doi:10.1155/2019/4602052.
    • Chicago/Turabian: Humanities:
      Gilseung Ahn, Myunghwan Park, You-Jin Park, and Sun Hur. “Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry.” Mathematical Problems in Engineering, 2019. doi:10.1155/2019/4602052.
    • Vancouver/ICMJE:
      Gilseung Ahn, Myunghwan Park, You-Jin Park, Sun Hur. Interactive Q-Learning Approach for Pick-and-Place Optimization of the Die Attach Process in the Semiconductor Industry. Mathematical Problems in Engineering [Internet]. 2019 [cited 2019 Oct 23]; Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsdoj&AN=edsdoj.fc0569dea084dc9b10ba8b9d03e99c9&custid=s8280428