Control System

Additionally the system can be used as a temperature sensor and actor. By measurement of the cooling liquid‘s temperature at the inlet and outlet the temperature at the tool tip can be estimated. At the same time it is possible to take influence on the tool temperature by variation of the mass flow of cooling liquid.

Plan of the self-learning control system

Self-learning algorithms like artificial neural networks can be used to predict the process results (accuracy, surface and subsurface quality) or tool wear. With an intelligent control system the information can be used to influence the process parameters and optimise the result.

Resulting Effects:

  • Cost savings through increased tool life through minimized thermal shock
  • Improved accuracy and surface integrity through avoidance of cooling lubricant
  • Increased efficiency by higher cutting parameters through adapting tool temperature
  • Cost saving through avoidance of cooling lubricants
  • Minimized ecological damage and health risks