Automated and Systematic Digital Twins Testing for Industrial Processes-Reference-Cited by-同舟云学术

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Automated and Systematic Digital Twins Testing for Industrial Processes

Published:2023-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)
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Author:

Ma Yunpeng¹,Younis Khalil¹,Ahmed Bestoun S.¹,Kassler Andreas¹,Krakhmalev Pavel²,Thore Andreas³,Lindbäck Hans⁴

Affiliation:

1. Karlstad University,Dep. Mathematics & Computer Science,Karlstad,Sweden

2. Karlstad University,Dep. Materials Science,Karlstad,Sweden

3. RISE Research Institutes of Sweden,Smart Industrial Automation,Västerås,Sweden

4. Bharat Forge Kilsta AB,Karlskoga,Sweden

Funder

Vinnova

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10132157/10132158/10132216.pdf?arnumber=10132216

Reference21 articles.

1. A digital twin-driven approach towards traceability and dynamic control for processing quality

2. Digital twin-driven multi-variable process control of thermal manufacturing processes

3. Motion Planning for Industrial Robots using Reinforcement Learning

4. Digital twin for rapid damage detection of a fixed net panel in the sea

5. Deep reinforcement learning for process control: A primer for beginners;spielberg,2020

Cited by 1 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 Comprehensive Review of Digital Twin from the Perspective of Total Process: Data, Models, Networks and Applications;Sensors;2023-10-08

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