Digital Twin-driven multi-scale characterization of machining quality: current status, challenges, and future perspectives
Xiangfu Fu, Shuo Li, Hongze Song, Yuqian Lu
Abstract
The evolution of manufacturing towards intelligent and digital processes requires innovation in machining quality control. While current research primarily addresses single-scale quality control, it overlooks comprehensive multi-scale product quality characterization. Digital twin technology emerges as a potential solution. This review examines digital twin applications in machining quality control, highlighting limitations of traditional methods and exploring multi-scale quality characterization at macro, meso, and micro levels. It evaluates multi-scale quality changes during processing and summarizes comprehensive characterization methods across scales. The study concludes by discussing future prospects for digital twin technology in multi-scale machining quality control and optimization.