Study on the Thermal Characteristics of a Turning and Milling Machine Using Taguchi-FEM with ANOVA-Driven Search

Abstract

Turning and milling machines (TMMs) have diverse and complex heat sources, which pose challenges to understanding and accurately predicting their thermal behavior. This study established a transient 3D thermal model of the TMM using the Finite Element Method (FEM) to predict the temporal evolution of temperature and deformation fields. The FEM predictions were then compared with the experimental results from five machining scenarios for model validation, demonstrating accurate prediction of temperature and deformation with average errors of 0.9% and 5.59 μm, respectively. A comprehensive procedure was proposed to explore the thermal characteristics of TMMs and identify thermally critical components. This study employed a Taguchi-FEM approach along with sensitivity analysis to evaluate the significant contributing boundary conditions of TMMs to tool center point (TCP) deformation in the X, Y, and Z directions. An ANOVA-driven search was further proposed to identify thermal key points significantly impacting TCP deformation across directions and time intervals. Integrating both methods facilitated the identification of the TMM thermal critical regions. The spindle TCP’s thermal critical regions were most significantly influenced by the spindle component, followed by the milling cutter shaft component and then the right side of the base bed. Similarly, for the sub-spindle TCP, the highest impact came from the sub-spindle components, followed by the right side of the base bed and the milling cutter shaft components. The proposed procedure identified the significant regions for assisting evaluation in TMMs and reduced the number of required temperature monitoring points while optimizing their placements to minimize measurement costs.