The Other Kind of Machine Learning: Modeling Worker State for Optimal Training of Novices in Complex Industrial Processes
Sprache des Titels:
Englisch
Original Buchtitel:
ICETA 2018
Original Kurzfassung:
In the context of Industry 4.0, there is a strong
focus on man-machine interaction, and a push for ICT solutions
in industrial applications. One aspect of this are industrial
assistance systems, both to aid operators in their work and
to train novice workers in complex processes. Addressing the
latter purpose, in this work, a training station e-learning concept
is detailed, with the purpose to automatically teach a novice
worker the necessary steps to assemble an alpine ski without
the need for constant human supervision. It is designed to
observe and especially model the state of the trainee for optimal
support via delivery of instructional material and feedback
based on an evaluation of the trainee?s needs and behavior.
The training station is comprised of a work bench, displays to
deliver instructional material, and various sensors to monitor
both the trainee?s progress and overall state. To enable best
possible worker support, a model of worker state (Idle, Flow,
Busy, Overload) is proposed which is derived from analysis of the
sensor data. It enables the system to provide dynamic assistance
in which feedback is fine-tuned to meet the trainee?s needs and
deliver information precisely, and only when it is needed.
Forschungs-