Advanced sensor-based maintenance in real-world exemplary cases-Reference-Cited by-同舟云学术

Advanced sensor-based maintenance in real-world exemplary cases

Published:2020-07-21 Issue:4 Volume:61 Page:537-553
ISSN:0005-1144
Container-title:Automatika
language:en
Short-container-title:Automatika

Author:

Albano Michele¹^ORCID,Lino Ferreira Luis²,Di Orio Giovanni³^ORCID,Maló Pedro³^ORCID,Webers Godfried⁴,Jantunen Erkki⁵,Gabilondo Iosu⁶,Viguera Mikel⁷,Papa Gregor⁸^ORCID

Affiliation:

1. Department of Computer Science, Aalborg University, Aalborg, Denmark

2. CISTER, ISEP, Polytechnic Institute of Porto, Porto, Portugal

3. UNINOVA / NOVA School of Science and Technology (FCT NOVA), Lisboa, Portugal

4. Philips Healthcare, Amsterdam, Netherlands

5. VTT Technical Research Centre of Finland, Espoo, Finland

6. Ikerlan, Arrasate-Mondragón, Spain

7. Koniker, Arrasate-Mondragón, Spain

8. Jožef Stefan Institute, Ljubljana, Slovenia

Funder

FCT/MEC

Slovenian Research Agency

ERDF

ECSEL JU

EU ECSEL JU

Publisher

Informa UK Limited

Subject

General Computer Science,Control and Systems Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/00051144.2020.1794192

Reference58 articles.

1. Schwab Klaus. 2017. ‘The fourth industrial revolution’, 2017, Crown Business, New York.

2. Productive 4.0 – A European co-funded innovation and lighthouse project on Digital Industry. Available from: https://productive40.eu/.

3. A review of monitoring methods for predictive maintenance of electric power transformers based on dissolved gas analysis

Cited by 6 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. Adaptive supervisory control for a class of Petri nets with bimodal transitions;Information Sciences;2023-12

2. A Data-Based Tool Failure Prevention Approach in Progressive Die Stamping;Journal of Manufacturing and Materials Processing;2023-05-08

3. Application of sensor data based predictive maintenance and artificial neural networks to enable Industry 4.0;Advances in Manufacturing;2023-03-04

4. Non-intrusive Anomaly Detection of Industrial Robot Operations by Exploiting Nonlinear Effect;Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies;2022-12-21

5. A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing;Computers & Industrial Engineering;2022-02