Methodology for enabling dynamic digital twins and virtual model evolution in industrial robotics - a predictive maintenance application-Reference-Cited by-同舟云学术

Methodology for enabling dynamic digital twins and virtual model evolution in industrial robotics - a predictive maintenance application

Published:2023-02-08 Issue:7 Volume:36 Page:947-965
ISSN:0951-192X
Container-title:International Journal of Computer Integrated Manufacturing
language:en
Short-container-title:International Journal of Computer Integrated Manufacturing

Author:

Aivaliotis Panagiotis¹^ORCID,Arkouli Zoi¹,Georgoulias Konstantinos¹,Makris Sotiris¹^ORCID

Affiliation:

1. Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, Patras, Greece

Funder

European Institute of Innovation & Technology

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Computer Science Applications,Mechanical Engineering,Aerospace Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/0951192X.2022.2162591

Reference48 articles.

1. ABB. 2021. ”Model Predictive Control - MPC Technology from ABB - What is New” ABB, https://new.abb.com/industrial-software/features/model-predictive-control-mpc/digital-twin-applications

2. Power and force limiting on industrial robots for human-robot collaboration

3. Degradation curves integration in physics-based models: Towards the predictive maintenance of industrial robots

4. Methodology for enabling Digital Twin using advanced physics-based modelling in predictive maintenance

5. The use of Digital Twin for predictive maintenance in manufacturing

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