本团队唐学峰副教授与合作者在International Journal of Machine Tools and Manufacture发表研究论文。

摘要：Defects in metal-forming create numerous bottleneck issues related to product quality, properties and performance, productivity, production cost, environmental friendliness, and sustainability. Effectively addressing defect issues in the up-front design process via prediction and avoidance of defect formation is the most critical and challenging issue in metal-forming based product development. In this paper, vital insights into defect classification, formation mechanisms, modelling/prediction, and avoidance principles and strategies in metal-forming are orchestrated and articulated. First, almost all the potential defects in metal-forming are exemplified and classified into three categories, viz., stress-induced, flow-induced, and microstructure-related defects. For each defect category, its influencing factors, formation mechanisms, and analysis approaches are delineated. Additionally, the countermeasures are articulated from the aspects of defect identification, control, avoidance or elimination by employing different state-of-the-art techniques, including in-process sensing/monitoring/detection, data-based modelling and online adaptive control. Finally, perspective insights into defect analysis, prediction, and avoidance are orchestrated and presented, focusing on innovative process developments, real-time in-process monitoring, physics-informed and data-driven through-process modelling, and strategies for intelligent and sustainable manufacturing.