Digital twins in mechatronics: From model-based control to predictive maintenance

Koen Classens; W.P.M.H.Maurice Heemels; Tom Oomen

doi:10.1109/DTPI52967.2021.9540144

Digital twins in mechatronics: From model-based control to predictive maintenance

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Fault diagnosis systems are essential in precision mechatronics to facilitate maintenance and to minimize downtime. The aim of this paper is to describe the current trend in control for precision mechatronics and the related future challenges for digital twin-assisted predictive maintenance as well as recently developed approaches. The future generation of fault diagnosis systems is envisaged to rely on identified physics-based models, enriched by the available real-time data from a large number of sensors and actuators.

Original language	English
Title of host publication	2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI)
Publisher	Institute of Electrical and Electronics Engineers
Pages	336-339
Number of pages	4
ISBN (Electronic)	9781665433372
DOIs	https://doi.org/10.1109/DTPI52967.2021.9540144
Publication status	Published - 22 Sept 2021
Event	1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021 - Beijing, China Duration: 15 Jul 2021 → 15 Aug 2021 Conference number: 1 https://www.dtpi.org/

Conference

Conference	1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021
Abbreviated title	DTPI 2021
Country/Territory	China
City	Beijing
Period	15/07/21 → 15/08/21
Internet address	https://www.dtpi.org/

Funding

ACKNOWLEDGEMENT This work is supported by Topconsortia voor Kennis en Innovatie (TKI), and is supported by ASML Research, Veld-hoven, The Netherlands.

Keywords

Digital twin
Fault diagnosis
Mechatronics
Predictive maintenance

Access to Document

10.1109/DTPI52967.2021.9540144

Cite this

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title = "Digital twins in mechatronics: From model-based control to predictive maintenance",

abstract = "Fault diagnosis systems are essential in precision mechatronics to facilitate maintenance and to minimize downtime. The aim of this paper is to describe the current trend in control for precision mechatronics and the related future challenges for digital twin-assisted predictive maintenance as well as recently developed approaches. The future generation of fault diagnosis systems is envisaged to rely on identified physics-based models, enriched by the available real-time data from a large number of sensors and actuators.",

keywords = "Digital twin, Fault diagnosis, Mechatronics, Predictive maintenance",

author = "Koen Classens and W.P.M.H.Maurice Heemels and Tom Oomen",

note = "Funding Information: ACKNOWLEDGEMENT This work is supported by Topconsortia voor Kennis en Innovatie (TKI), and is supported by ASML Research, Veld-hoven, The Netherlands. Publisher Copyright: {\textcopyright} 2021 IEEE.; 1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021, DTPI 2021 ; Conference date: 15-07-2021 Through 15-08-2021",

year = "2021",

month = sep,

day = "22",

doi = "10.1109/DTPI52967.2021.9540144",

language = "English",

pages = "336--339",

booktitle = "2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI)",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

url = "https://www.dtpi.org/",

}

Classens, K, Heemels, WPMHM & Oomen, T 2021, Digital twins in mechatronics: From model-based control to predictive maintenance. in 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI)., 9540144, Institute of Electrical and Electronics Engineers, pp. 336-339, 1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021, Beijing, China, 15/07/21. https://doi.org/10.1109/DTPI52967.2021.9540144

Digital twins in mechatronics: From model-based control to predictive maintenance. / Classens, Koen; Heemels, W.P.M.H.Maurice ; Oomen, Tom.
2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI). Institute of Electrical and Electronics Engineers, 2021. p. 336-339 9540144.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Digital twins in mechatronics

T2 - 1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

AU - Classens, Koen

AU - Heemels, W.P.M.H.Maurice

AU - Oomen, Tom

N1 - Conference code: 1

PY - 2021/9/22

Y1 - 2021/9/22

N2 - Fault diagnosis systems are essential in precision mechatronics to facilitate maintenance and to minimize downtime. The aim of this paper is to describe the current trend in control for precision mechatronics and the related future challenges for digital twin-assisted predictive maintenance as well as recently developed approaches. The future generation of fault diagnosis systems is envisaged to rely on identified physics-based models, enriched by the available real-time data from a large number of sensors and actuators.

AB - Fault diagnosis systems are essential in precision mechatronics to facilitate maintenance and to minimize downtime. The aim of this paper is to describe the current trend in control for precision mechatronics and the related future challenges for digital twin-assisted predictive maintenance as well as recently developed approaches. The future generation of fault diagnosis systems is envisaged to rely on identified physics-based models, enriched by the available real-time data from a large number of sensors and actuators.

KW - Digital twin

KW - Fault diagnosis

KW - Mechatronics

KW - Predictive maintenance

UR - https://www.scopus.com/pages/publications/85116150378

U2 - 10.1109/DTPI52967.2021.9540144

DO - 10.1109/DTPI52967.2021.9540144

M3 - Conference contribution

AN - SCOPUS:85116150378

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BT - 2021 IEEE 1st International Conference on Digital Twins and Parallel Intelligence (DTPI)

PB - Institute of Electrical and Electronics Engineers

Y2 - 15 July 2021 through 15 August 2021

ER -

Digital twins in mechatronics: From model-based control to predictive maintenance

Abstract

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Keywords

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