Work

Digital Twin-driven multi-scale characterization of machining quality: current status, challenges, and future perspectives

Year: 2024

Type: article

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.

Source: Robotics and Computer-Integrated Manufacturing

DOI: 10.1016/j.rcim.2024.102902

Authors: Xiangfu Fu, Shuo Li, Hongze Song, Yuqian Lu

Institutions: Harbin University of Science and Technology, University of Auckland

Language: English

Topic: Digital Transformation in Industry

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Estimated APC paid: $4,410