Thermal analytical modeling of machine tool structural components via dual-layer equivalence

Abstract

Precision machine tools are sensitive to thermal effects. Thermal deformation of machine tool structural components can lead to changes in the relative pose between the spindle tool and the workpiece, causing thermally induced machining errors. Gaining insight into the mechanistic correlation between critical thermal condition parameters of heat sources and thermal errors in machine tools is essential to elevate the design of machine tool thermal attributes. To address this issue, this paper proposes a dual-layer equivalent analytical modeling method for characterizing the thermal properties of structural components. The construction of the temperature field analytical model for the dual-layer equivalent structure is achieved by setting and handling different interlayer heat flows and temperature boundary conditions. The dual-layer equivalent approach simplifies complex structural components into top and bottom layers, providing a more flexible and accurate capability for characterizing the thermal properties of structural components. This modeling method enables rapid prediction and evaluation of machine tool thermal characteristics. Furthermore, based on this analytical approach, the calculation method of sensitivity coefficient of thermal power to thermal error is proposed to elucidate the mapping relationship between different thermal condition parameters and thermal errors. This method facilitates the fast and accurate prediction of six thermally induced errors under various thermal conditions. Experimental results demonstrate that the key point temperature deviation predicted using the dual-layer analytical modeling method is less than 0.8 °C, and the thermally induced axial linear error deviation is less than 1.8 μm. The dual-layer analytical modeling approach introduced in this study presents a versatile technique applicable to enhancing the design and control of machine tool thermal characteristics, holding significant potential for advancing the stability of machine tools thermal accuracy.