Abstract
In CNC machine tools, transient temperature variation in the headstock assembly is the major contributors for spindle thermal error. The compensation of thermal error is critical for ensuring the accuracy of machine tool. The performance of an error compensation system depends largely on the accuracy and robustness of the thermal error model. In the present work, a robust thermal error model is developed for minimizing the error in lateral direction of the spindle which significantly influences the geometrical accuracy of the workpiece. Analysis-of-variance (ANOVA) is applied to the results of the experiments in determining the percentage contribution of each individual temperature key point against a stated level of confidence. Based on the analysis of existing approaches for thermal error modeling of machine tools, an approach of LASSO (least absolute shrinkage and selection operator) is proposed in order to avoid the multi collinearity problem. The proposed method is an innovative variable selection method to remove redundant or unimportant temperature key points in the linear thermal error model and minimize the residual sum of squares. The predictive error model is found to have better robustness and accuracy in comparison to the combination of grey correlation and step wise linear regression for error compensation of CNC lathe. Keywords: Analysis Of Variance (ANOVA), CNC Machine Tool, Grey Correlation Analysis (GCA), Headstock Assembly, LASSO Regression, Mean Absolute Deviation (MAD), Mean Square Error (MSE), Robustness, Standard Deviation (SD), Thermal Error.
Highlights
The machine tool accuracy directly affects the dimensional accuracy of the machined products
The transient variation of temperature and thermal error in the headstock assembly of CNC turning centre has been investigated through experimentation
In the process of thermal error modeling, the application of LASSO regularized regression led to the reduction of number of temperature key points from 13 to 3
Summary
The machine tool accuracy directly affects the dimensional accuracy of the machined products. Thermal error is caused by the accumulation of the deformation of machine tool elements, which stems from nonuniform temperature change in machine tool structure. The minimization of the thermal errors of machine tools is concentrated on the three aspects [3, 4]; reduction in the heat sources, design of a thermally robust structure and compensation of thermal deformation. Among these solutions, the reduction in heat sources is not possible beyond a certain limit as friction between parts in motion would certainly generate some heat. Compensation after thermal deformation gains success these days both on account of its implementation as well as its cost-effectiveness [1]
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