Digital Twins for Energy-Efficient Manufacturing

被引:1
作者
Mohamed, Nader [1 ]
Lazarova-Molnae, Sanja [2 ,3 ]
Al-Jaroodi, Jameela [4 ]
机构
[1] Penn Western Hosp, Dept Comp Sci & Informat Syst, Calif, CA 15419 USA
[2] Karlsruhe Inst Technol, Inst Appl Informat & Formal Descript Methods, Karlsruhe, Germany
[3] Univ Southern Denmark, Fac Engn, Odense, Denmark
[4] Robert Morris Univ, Dept Engn, Pittsburgh, PA USA
来源
2023 IEEE INTERNATIONAL SYSTEMS CONFERENCE, SYSCON | 2023年
关键词
Digital Twin; Energy Efficiency; Smart Factory; Industry; 4.0; Modeling; Simulation; MACHINE-TOOLS; INDUSTRY; RELIABILITY; INTERNET; SYSTEMS;
D O I
10.1109/SysCon53073.2023.10131066
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Some manufacturing industries consume massive energy for their manufacturing and logistics processes. The costs of manufacturing can increase significantly as the energy cost increases. Such increase amplifies the final cost of the created products on the consumers. This makes finding different approaches that utilize innovative technologies to improve energy efficiency in manufacturing extremely important. This paper investigates how digital twins can be utilized to enable improved energy efficiency in manufacturing. Different applications of digital twins for energy-efficient manufacturing are investigated. In addition, the paper discusses some challenges of utilizing digital twins for this purpose. A framework for utilizing digital twins for energy-efficient manufacturing is also discussed.
引用
收藏
页数:7
相关论文
共 43 条
[1]  
Al-Jaroodi Jameela, 2018, ACM SIGBED Review, V15, P29, DOI 10.1145/3292384.3292389
[2]  
Almada-Lobo F., 2016, J INNOVATION MANAGEM, V3, P16, DOI [https://doi.org/10.24840/2183-0606_003.004_0003, DOI 10.24840/2183-0606_003.004_0003, 10.24840/2183-0606_003.004_0003]
[3]   Energy Efficiency of Manufacturing Processes: A Critical Review [J].
Apostolos, Fysikopoulos ;
Alexios, Papacharalampopoulos ;
Georgios, Pastras ;
Panagiotis, Stavropoulos ;
George, Chryssolouris .
FORTY SIXTH CIRP CONFERENCE ON MANUFACTURING SYSTEMS 2013, 2013, 7 :628-633
[4]   Energy economics in the manufacturing industry: A return on investment strategy [J].
Brundage, Michael P. ;
Chang, Qing ;
Zou, Jing ;
Li, Yang ;
Arinez, Jorge ;
Xiao, Guoxian .
ENERGY, 2015, 93 :1426-1435
[5]   Machine reliability and preventive maintenance planning for cellular manufacturing systems [J].
Das, K. ;
Lashkari, R. S. ;
Sengupta, S. .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 183 (01) :162-180
[6]   Towards energy and resource efficient manufacturing: A processes and systems approach [J].
Duflou, Joost R. ;
Sutherland, John W. ;
Dornfeld, David ;
Herrmann, Christoph ;
Jeswiet, Jack ;
Kara, Sami ;
Hauschild, Michael ;
Kellens, Karel .
CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2012, 61 (02) :587-609
[7]   Maintenance for Energy efficiency: A Review [J].
Firdaus, N. ;
Samat, H. A. ;
Mohamad, N. .
INTERNATIONAL CONFERENCE ON RECENT ADVANCES IN INDUSTRIAL ENGINEERING AND MANUFACTURING, 2019, 530
[8]   A framework for data-driven digitial twins of smart manufacturing systems [J].
Friederich, Jonas ;
Francis, Deena P. ;
Lazarova-Molnar, Sanja ;
Mohamed, Nader .
COMPUTERS IN INDUSTRY, 2022, 136
[9]   Towards Data-Driven Reliability Modeling for Cyber-Physical Production Systems [J].
Friederich, Jonas ;
Lazarova-Molnar, Sanja .
12TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 4TH INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS, 2021, 184 :589-596
[10]  
Grieves MW, 2019, PROG ASTRONAUT AERON, V256, P175