Digital Twins for Energy-Efficient Manufacturing-Reference-Cited by-同舟云学术

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Digital Twins for Energy-Efficient Manufacturing

Published:2023-04-17 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Systems Conference (SysCon)
language:
Short-container-title:

Author:

Mohamed Nader¹,Lazarova-Molnar Sanja²,Al-Jaroodi Jameela³

Affiliation:

1. Pennsylvania Western University,Department of Computer Science and Information Systems,California,PA,USA

2. Karlsruhe Institute of Technology,Institute of Applied Informatics and Formal Description Methods,Karlsruhe,Germany

3. Robert Morris University,Department of Engineering,Pittsburgh,PA,USA

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10131045/10131046/10131066.pdf?arnumber=10131066

Reference43 articles.

1. Towards energy and resource efficient manufacturing: A processes and systems approach

2. Automating Reliability Analysis: Data-driven Learning and Analysis of Multistate Fault Trees

3. Process chain simulation to foster energy efficiency in manufacturing

4. Data-Driven Fault Tree Modeling for Reliability Assessment of Cyber-Physical Systems

5. Implementing Key Performance Indicators for Energy Efficiency in Manufacturing

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Framework for Energy-Efficient Manufacturing using Digital Twins;2024 International Conference on Smart Applications, Communications and Networking (SmartNets);2024-05-28

2. Predictive Analytics for Digital Twins: The Concept and Systems Applications;2024 7th International Conference on Information and Computer Technologies (ICICT);2024-03-15

3. Essential Data Requirements for Industrial Energy Efficiency with Digital Twins: A Case Study Analysis;Procedia Computer Science;2024

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