{"title":"Digital Twin-driven multi-scale characterization of machining quality: current status, challenges, and future perspectives","authors":"Xiangfu Fu, Shuo Li, Hongze Song, Yuqian Lu","doi":"10.1016/j.rcim.2024.102902","DOIUrl":null,"url":null,"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.","PeriodicalId":21452,"journal":{"name":"Robotics and Computer-integrated Manufacturing","volume":"198 1","pages":""},"PeriodicalIF":9.1000,"publicationDate":"2024-11-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Robotics and Computer-integrated Manufacturing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1016/j.rcim.2024.102902","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
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.
期刊介绍：
The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.
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