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Approach to improving training of human workers in industrial applications through the use of Intelligence Augmentation and Human-in-the-Loop

 
: Mättig, Benedikt; Foot, Hermann

:

Song, Y. ; IEEE Education Society:
15th International Conference on Computer Science and Education, ICCSE 2020 : August 18-20, online
Piscataway, NJ: IEEE, 2020
ISBN: 978-1-72817-267-5
ISBN: 978-1-72817-266-8
ISBN: 978-1-72817-268-2
S.283-288
International Conference on Computer Science & Education (ICCSE) <15, 2020, Online>
Englisch
Konferenzbeitrag
Fraunhofer IML ()
training; Human Worker; augmentation

Abstract
Training employees for industrial processes is a major challenge in the industry. There are different approaches to meet this challenge. In practice, however, we often observe that experienced employees are seconded to train new employees in processes. This is very expensive and does not allow intensive training. Digital assistance systems can support the training process to a certain extent, but they do not have the detailed experience knowledge that the older employees have. In particular, the implicit knowledge of experienced employees cannot be digitally mapped with the classic solutions. At this point, the approach presented here is intended to support the training process by using Intelligence Augmentation to combine artificial and human intelligence in order to design an assistance system capable of learning, which should considerably improve the training of inexperienced employees. How this solution is designed in detail is described in this article.

: http://publica.fraunhofer.de/dokumente/N-614588.html