Thermal parameter optimisation for accurate finite element based on simulation of machine tools

The need for high-speed/high-precision machine tools is swiftly increasing in response to the growth of production technology that necessitates high- recision parts and high productivity. The influence of thermally induced errors in machine tools can have a much greater influence on the dimensional tolerances of the final products produced as compared to geometric and cutting force errors. Therefore, to maintain high accuracy of machine tool, it requires an accurate method of thermal error control or compensation using a detailed model. The thermal errors of machine tools are induced by the propagation of heat through the structure of the machine due to excitation of internal and external heat sources such as belt drives, motors and bearings. There has been significant research effort to model thermal errors of machine tools in recent decades. The utilised techniques have proved their capabilities with excellent thermal prediction and compensation results but they often involve significant effort for effective implementation with constraints for complexity, robustness, and cost. One of the most significant drawbacks of modelling machine behaviour using Finite Element Analysis (FEA) is the difficulty of accurately obtaining the characteristic of heat transfer, such as heat power of machine tool heat sources and the various boundary conditions. The aims of this research to provide reliable techniques to obtain heat transfer coefficients of machine tools in order to improve the accuracy of FEA simulations. FEA is used to simulate the thermal characteristics of spindle system of small Vertical Machining Centre (VMC) using SolidWorks Simulation software. Most FEA models of machine tools employ the general prediction technique based on formulae, provided by OEMs, to identify many of the boundary conditions associated with simulating thermal error in machine tools. The formulae method was used to identify the heat transfer coefficients of a small VMC feed drive system. Employing these values allowed FEA to be used to simulate the thermal characteristics of the feed drive model. In addition, an alternative efficient methodology, based on energy balance calculations and thermal imaging, was used to obtain the heat transfer coefficients of the same feed drive system. Then the parameters obtained were applied to the FEA model of the system and validated against experimental results. The residual thermal error was reduced to just 20 % when the energy balance method was employed and compared with a residual of 30 %, when the formulae method was employed. The existing energy balance method was also used to obtain the heat transfer coefficients of the headslide on a small VMC based on thermal imaging data. Then FEA model of the headslide of VMC was created and simulated. There was significant reduction in the thermal error but significant uncertainties in the method were identified suggesting that further improvements could be made. An additional novel Two Dimensional (2D) optimisation technique based on thermal imaging data was created and used to calibrate the calculated heat transfer coefficients of the headslide of a small sized machine tool. In order to optimise the heat power of various heat sources, a 2D model of surface temperature of the headslide was created in Matlab software and compared against the experimental data both spatially across a plane and over time in order to take into account time varying heat loads. The effectiveness of the technique was proved using FEA models of the machine and comparison with test data from the machine tool. Significant improvement was achieved with correlation of 85 % between simulated thermal characteristics and the experimental dat

Thermal Error Modelling of a CNC Machine Tool Feed Drive System using FEA Method

Recirculating ball screw systems are commonly used in machine tools and are one of the major heat sources which cause considerable thermal drift in CNC machine tools. Finite Element Analysis (FEA) method has been used successfully in the past to model the thermal characteristics of machine tools with promising results. Since FEA predictions are highly dependent on the efficacy of numerical parameters including the surrounding Boundary Conditions (BC), this study emphasises on an efficient modelling method to obtain optimised numerical parameters for acquiring a qualitative response from the feed drive system model. This study was performed on a medium size Vertical Machining Centre (VMC) feed drive system in which two parameter dentification methods have been employed; the general prediction method based on formulae provided by OEMs, and the energy balance method. The parameters obtained from both methods were applied to the FEA model of the machine feed drive system and validated against experimental results. Correlation with which was increased from 70 % to 80 % using the energy balance method

Thermal error modelling of a three axes vertical milling machine using Finite element analysis (FEA)

Thermal errors in machine tools have a detrimental effect on the accuracy of components they produce. In order to reduce the influence of thermal errors, the propagation of heat through the structure of the machine needs to be understood. The modelling of thermal error of small three axes vertical milling centre (VMC) machine tools is introduced in this paper. Firstly, a thermal imaging camera and non-contact displacement transducer (NCDT) sensors were used to measure the temperature and thermal deformation in X, Y, Z axes respectively during spindle heating and cooling cycles. Secondly, a model of the VMC was created using SolidWorks software and simulated using finite element analysis (FEA). The boundary conditions are calculated according to measured parameters like, temperatures of machine structure, heat transfer coefficients and ambient temperature. Of particular importance is the heat power of heat generating components in the machine such as the main spindle motor and bearings. These parameters vary with machine use and are calculated using energy balance calculations and thermal imaging data. Finally, the FEA simulated results are obtained and are in close correlation with the experimental results. Such accurate FEA simulations permit offline assessments to be made of temperature gradients and displacements in machine tools structures, reducing the need for expensive on-line testing. Furthermore, correlation coefficient analysis is employed to validate the simulated model temperature; the thermal error was reduced up to 90%, from 3

Machine structure simulation using FEA and optimised thermal parameters

Continuous usage of machine tools during manufacturing processes causes heat generation in the moving elements, resulting in distortion of the machine tool structure. Simulation of this thermal behaviour can be a powerful tool for supporting the design process and predicting errors. Determining accurate heat transfer parameters is needed to improve the prediction accuracy of the physical thermal models. First, the energy balance technique was used to calculate the parameters empirically. Due to uncertainties in the boundary conditions for this technique, an additional novel 2D optimisation technique based on thermal imaging data was used to calibrate the calculated parameters. The effectiveness of the technique was proved using FEA models of the machine. Good correlation of up to 80 % was achieved between simulated thermal characteristics and the experimental data.</p