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Human-Machine-Teaming: Teaching Machine, Learning Machine

Based on Artificial Intelligence an «Intelligent Assistant» is developed for grinding processes, that allows for an innovative collaboration of humans and machines.

Excellent grinding requires the adjustment of multiple interacting parameters. Many of these are not numerically controlled. Their fine-tuning may be specific to a machine and sensitive to a context.

Hence, parameter adjustment is not easily transferable between machines. Rather than by algorithmic this fine-tuning is dependent on tacit knowledge of experienced human operators.

Therefore, we aim at a human-machine teaming that combines human knowledge and machine capabilities. Doing so three core questions are addressed:

  • Learning machine: The intelligent assistant learns from the human and hence develops continuously.
  • Teaching machine: The intelligent assistant will not replace the human but rather support human learning.
  • Multi-collaboration: Human-machine teaming does not refer to individuals but rather to social systems of many people working together with many machines. Such, distributed knowledge is addressed, and systematic learning is supported.


Project Dates

Lead and Team
Prof. Dr. Toni Wäfler (Lead), Philipp Renggli
Funding
Innosuisse
Collaboration
ETH, Inspire, United Grinding Group, Designsensor
Duration
2020–2023


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