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Intelligent thermal compensation and multiscale topology optimization for sustainable CNC machine tools
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DOI：10.1007/s10845-026-02951-y.png)
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Abstract
En 中文
Thermal deformation of CNC machine tools is still among the key constraints on machining accuracy, energy efficiency, and sustainability. In this investigation, we present a cyber-physical system that combines real-time sensor-based thermal monitoring and digital twin-based finite element simulations to reduce thermal errors in high-speed machining processes. A low-cost AD590 sensor array was installed at thermally critical locations and experimentally validated against quartz thermometer measurements with a thermal compensation accuracy of up to 10%. In addition, a hybrid topology optimization technique integrating multiple scales was applied at the macro and micro levels for mass minimization, stiffness enhancement, and modal stability improvement. Compared with the reference design, the optimized configurations resulted in weight reductions of up to 13.6%, frequency improvements of up to 14%, and effective suppression of thermal deformation. The experimental and analytical results reveal a good correlation error of < 10% in the thermal, static, and dynamic regimes. The developed methodology presents scalable and smart approach to autonomous thermal control and lightweight structural enhancement in CNC systems, supporting the objective of sustainable manufacturing and the aims of Industry 4.0.
Keywords:
Thermal error compensation
Sustainable CNC
Experimental validation
Static stiffness
Multiscale topology optimization
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