Adaptive Coolant Control Cuts Energy Use in CAM Driven Machining

A collaborative follow up project by IFW Hannover, OPEN MIND Technologies, Kennametal, and DMG MORI demonstrates that adaptive coolant supply can be controlled directly from CAM data. By deriving coolant demand from the material removal rate and embedding this information in the NC code, the partners achieved substantial energy savings while maintaining machining performance.

The project builds on DMG MORI’s adaptive coolant supply concept by shifting coolant control to the CAM environment. The partners developed a cycle time and tool specific planning method for milling and drilling that outputs an adapted NC code through hyperMILL. This method estimates coolant demand based on material removal rates calculated during CAM planning, enabling a more accurate and efficient supply strategy. The work covered three stages: modeling coolant requirements, integrating the calculation logic into hyperMILL via Python scripting, and validating the approach on a DMG MORI DMU 40 eVo linear machining center. The demonstrator setup enabled both controlled test conditions and a direct comparison with conventional coolant strategies.

Coolant demand modeling and programming

The coolant demand model relies on the correlation between rising material removal rates and increasing heat and chip generation. This relationship provides a practical basis for calculating coolant requirements using standard CAM data. Kennametal supplied reference data for each tool’s maximum material removal rate. In addition, pressure, flow rate, and pump power consumption were measured to establish characteristic curves for each tool under specific hydraulic conditions.

To implement the variable coolant flow in CAM, the team used hyperMILL’s Python API. During stock removal simulation, the cutting parameters of each machining line are evaluated and combined with tool metadata to calculate the material removal rate. The IFW module then determines the necessary coolant flow, after which a smoothing routine prevents abrupt changes along the toolpath. The resulting NC code includes the required flow control commands and can be transferred directly to the machine.

Verification on the machining center

Validation tests were conducted on a demonstrator part made of 11SMn30+C free cutting steel, involving milling, drilling, tapping, and broaching. Instead of adjusting coolant flow line by line, the tests applied an average flow value per machining step, which proved sufficient for stable operation. Pump energy consumption was recorded via the frequency converter and compared with conventional machining. The adaptive approach achieved energy savings of approximately 82 percent, with identical part quality.

The CAM based method also offers operational flexibility. Users can deactivate the adaptive mode when the mechanical flushing action of coolant is necessary, such as during drilling operations. The partners will continue developing the methodology to extend it to additional tool types, machining processes, and materials.
The study was published by Prof. Dr. Berend Denkena, Dr. Marc André Dittrich, Dr. Klaas Maximilian Heide, Dr. Alexander Krödel Worbes, Andreas Lieber, and Talash Malek (M. Sc.). It was also featured by Martin Winkler in VDI Z, issue 09/2025, under the title “Coolant Demand Planning Directly from the CAM System”.