数字孪生的合成数据生成:在缺乏数据的情况下实现生产系统分析

IF 3.7 3区 工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Paulo Victor Lopes, Leonardo Silveira, Roberto Douglas Guimaraes Aquino, Carlos Henrique Ribeiro, Anders Skoogh, Filipe Alves Neto Verri
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引用次数: 0

摘要

工业界越来越重视数据驱动的生产线数字双胞胎,特别是在规划、控制和优化应用方面。然而,由于缺乏有关制造系统的开放数据,这些数据的使用将受到限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Synthetic data generation for digital twins: enabling production systems analysis in the absence of data
Industry increasingly focuses on data-driven digital twins of production lines, especially for planning, controlling and optimising applications. However, the lack of open data on manufacturing sys...
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来源期刊
CiteScore
9.00
自引率
9.80%
发文量
73
审稿时长
10 months
期刊介绍: International Journal of Computer Integrated Manufacturing (IJCIM) reports new research in theory and applications of computer integrated manufacturing. The scope spans mechanical and manufacturing engineering, software and computer engineering as well as automation and control engineering with a particular focus on today’s data driven manufacturing. Terms such as industry 4.0, intelligent manufacturing, digital manufacturing and cyber-physical manufacturing systems are now used to identify the area of knowledge that IJCIM has supported and shaped in its history of more than 30 years. IJCIM continues to grow and has become a key forum for academics and industrial researchers to exchange information and ideas. In response to this interest, IJCIM is now published monthly, enabling the editors to target topical special issues; topics as diverse as digital twins, transdisciplinary engineering, cloud manufacturing, deep learning for manufacturing, service-oriented architectures, dematerialized manufacturing systems, wireless manufacturing and digital enterprise technologies to name a few.
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