ICTM Collaborative R&D 2024

Tool condition monitoring for autonomous decision support on machine tools

Can indirect tool monitoring detect non-uniform tool wear to support autonomous tool change?

Challenge and Motivation

  • Automated tool change triggered by indirect wear monitoring is beneficial for productivity and ecology.
  • Utilization of only internal signals in manufacturing has proven difficult, whereby chipping remains unconsidered in conventional assessment.


  • Extend tool usage by adoption of machine tool data and additional sensory for indirect tool wear monitoring.
  • Assess machining data using regression approaches for the detection of non-uniform tool wear.