A review of robust thermal error reduction of machine tools

Abstract

Thermal error reduction in machine tools has attracted increasing attention owing to its influence on the accuracy, productivity, and energy efficiency of machining processes. In several traditional studies, the thermal error has been modeled as a straightforward relationship between the heat input and the output machining error. However, the demand for thermal error reduction in complex practical conditions with the interactive variation of influencing factors has been increasing because energy saving and a predictive countermeasure for defects, even in transient conditions, are expected. Robust reduction in the thermal error under such complex conditions remains a challenging issue. This paper reviews the strategy and methodology for realizing robust thermal error reduction considering the variation in influencing factors. A comprehensive model of thermal error that considers the interaction of thermal and mechanical systems is described to provide an overview of the targeted topic. Specific methodologies published over the last 15 years, such as adaptive modeling and compensation, machine design optimization, and temperature control, are reviewed. We focus on the evolution of data-driven models and digital twin systems for thermal error compensation by describing their implementation frameworks. An open question regarding strategy selection for thermal error compensation considering uncertainty is discussed. This review reveals the current research gap and provides an outlook for future challenges in realizing real-time and adaptive thermal error compensation.