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Title: Towards AI-Assisted Smart Training Platform for Future Manufacturing Workforce
With the fast development of Industry 4.0, the ways in which manufacturing workers handle machines, materials, and products also change drastically. Such changes post several demanding challenges to the training of future workforce. First, personalized manufacturing will lead to small batch and fast changing tasks. The training procedure must demonstrate agility. Second, new interfaces to interact with human or robots will change the training procedure. Last but not least, in addition to handling the physical objects, a worker also needs to be trained to digest and respond to rich data generated at the manufacturing site. To respond to these challenges, in this paper we describe the design of an AI-assisted training platform for manufacturing workforce. The platform will collect rich data from both machines and workers. It will capture and analyze both macro and micro movement of trainees with the help of AI algorithms. At the same time, training for interaction with robot/cobot will also be covered. Mixed reality will be used to create in-situ experiences for the trainee.
Authors:
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Award ID(s):
1937010 1840080
Publication Date:
NSF-PAR ID:
10184361
Journal Name:
AAAI 2020 Spring Symposium, AI in Manufacturing
Sponsoring Org:
National Science Foundation
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