过程(计算)
计算机科学
数据科学
生产(经济)
工业生产
系统工程
工业工程
制造工程
过程管理
工程类
操作系统
宏观经济学
经济
凯恩斯经济学
作者
Thomas Bergs,Dirk Biermann,Kaan Erkorkmaz,Rachid M’Saoubi
出处
期刊:CIRP Annals
[Elsevier]
日期:2023-01-01
卷期号:72 (2): 541-567
被引量:5
标识
DOI:10.1016/j.cirp.2023.05.006
摘要
Collecting and utilizing data in industrial production are becoming increasingly important. One promising approach to utilize data is the concept of digital twin (DT). DTs are virtual representations of physical assets, updated by real data and enhanced by models. This paper provides an overview of DTs for cutting processes. After giving a definition, we discuss requirements derived from representative use cases. As process models are central for DT creation, we present an overview of the latest research as well as conditions for how it can be implemented in industrial environments. The paper concludes with main challenges for future research.
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