Bio-based insulation materials and model predictive control of active cooling systems in machine tools

The adoption of biological principles and materials plays a decisive role in the conversion to sustainable production technologies. Measures for the biological transformation of a machine tool were implemented following the example of warm-blooded animal, which automatically control their core temperature and, depending on their habitat, possess an insulating layer of fat. In this work, thermal insulation measures were implemented on machine tools using renewable materials and their effects were evaluated. Insulation materials of petrochemical origin such as polystyrene (Styrofoam) were replaced by alternatives made of mycelium with comparable heat insulating properties. On the lower machine bed, a slowdown of the cooling rate was observed after application of insulation materials at external temperature drops. The insulation between the machine bed and the control cabinet was also found to reduce tool centre point (TCP) displacement. This cost-efficient measure reduces the error during the process and the effort required to correct the linear axes and to heat and cool the machine. To homogenize the temporal and spatial temperature profile of machine tools, a control system was developed to compensate for thermally induced errors by means of adaptive active cooling. Therefore, a model predictive control using an embedded artificial intelligence (AI) model to forecast the structural temperature development was implemented. Through a hybrid training database combining experimental and simulative data series, a both flexible and precise determination of the thermal system behaviour could be achieved. On a real production machine, the active cooling system is divided into five individually controllable and adjustable cooling circuits. This approach allows cooling the machine structure according to time and local demand to minimize thermally induced TCP displacement under variable operating conditions. This paper serves to define and evaluate possibilities and requirements for the integration of bio-based insulation materials and control algorithms for homoiothermic conditions in production machines.