MADE Digital WP5.3 - Designing Self-Configuring and Self-Learning Smart Factories

  • Bøgh, Simon (CoPI)
  • Chrysostomou, Dimitris (CoPI)
  • Anguiozar, Nerea Urrestilla (Project Participant)
  • Andersen, Rasmus Skovgaard (Project Participant)
  • Arexolaleiba, Nestor Arana (Project Participant)

Project Details

Description

In the smart factory, all machines, robots and systems are connected and can talk and interact with each other. The digital technologies tie all business processes together in the organization and create a production that is constantly adapting to new demands from customers, suppliers and the outside world.

In MADE Digital work package 5, Smart Factories, we work on how digital technologies can be applied in Danish companies to create smarter production.

Specifically, in WP5.3, the research work is concerned with developing adaptive learning algorithms enabling robots to adapt to variations in input, continuously perform corrections during processing and adjust processes based on the quality of the produced output.

Layman's description

Our research is focus on introducing self-learning capabilities in smart factories to optimize industrial processes in food manufacturing.
Short titleMADE Digital WP5.3
StatusFinished
Effective start/end date01/03/201731/12/2019

Keywords

  • made digital
  • self-learning factories
  • Reinforcement Learning
  • smart factories

Activities

  • 1 Organisation or participation in workshops, courses, or seminars

Special Session on Deep Learning As a Mean for Enabling Self-Learning and Self-Optimizing Capabilities in Real-World Industrial Applications

Simon Bøgh (Organizer), , Nestor Arana-Arexolaleiba (Organizer), & Dimitrios Chrysostomou (Organizer)

14 Jan 2020

Activity: Attending an eventOrganisation or participation in workshops, courses, or seminars

Research Output

  • 3 Article in proceeding

Transferring Human Manipulation Knowledge to Robots with Inverse Reinforcement Learning

Hansen, E. B., Andersen, R. E., Madsen, S. & Bøgh, S., 2020, (Accepted/In press) Proceedings of the 2020 IEEE/SICE International Symposium on System Integration, SII 2020. IEEE, p. 933-937 5 p. 9025873. (Proceedings of the 2020 IEEE/SICE International Symposium on System Integration).

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

File
  • 32 Downloads (Pure)

    Self-learning Processes in Smart Factories: Deep Reinforcement Learning for Process Control of Robot Brine Injection

    Andersen, R. E., Madsen, S., Barlo, A. B. K., Blegebrønd Johansen, S., Nør, M., Andersen, R. S. & Bøgh, S., 2019, 29th International Conference on Flexible Automation and Intelligent Manufacturing: FAIM 2019. Elsevier, Vol. 38. p. 171-177 7 p. (Procedia Manufacturing).

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

    Open Access
    File
  • 41 Downloads (Pure)

    Transferring Human Manipulation Knowledge to Industrial Robots Using Reinforcement Learning

    Arana-Arexolaleibo, N., Anguiozar, N. U., Chrysostomou, D. & Bøgh, S., 2019, 29th International Conference on Flexible Automation and Intelligent Manufacturing: FAIM 2019. Elsevier, Vol. 38. p. 1508 - 1515 8 p. (Procedia Manufacturing, Vol. 38).

    Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

    Open Access
    File
  • 38 Downloads (Pure)