TY - GEN
T1 - Application of Digital Twin Technology in Asset Management
T2 - UNIfied Conference of International Conference on Damage Assessment of Structures, DAMAS 2025, International Conference on Maintenance Engineering, IncoME 2025 and The Efficiency and Performance Engineering, TEPEN 2025
AU - Huang, Chiheng
AU - Duan, Fang
AU - Graja, Oussama
AU - Wang, Hongjun
AU - Yang, Wenxian
AU - Cattley, Robert
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026/1/3
Y1 - 2026/1/3
N2 - The concept of digital twins has been proposed for more than two decades. With the progression of Industry 4.0, digital twin technologies have attracted increasing interest from researchers. It has been widely implemented across various industries for solving problem like condition monitoring, fault diagnosis, remaining useful life prediction, performance and maintenance strategy optimization, decision making, etc. Given this variety, each digital twin may have unique purposes and applications and can vary in complexity. However, the current literature lacks a comprehensive classification model for digital twins in engineering asset management applications. This paper offers a comprehensive review of the current state and development of digital twin technology, beginning with a detailed introduction that covers its origins and technological evolution. It introduces a novel classification method that categorizes digital twins based on their capabilities and purposes, helping to systematically understand their diverse functions and applications. By integrating current knowledge with anticipated advancements, this article contributes significantly to the literature, proposing a roadmap for the future development of digital twins, with a particular focus on their application in monitoring conditions, diagnosing faults, and predicting failures in complex systems.
AB - The concept of digital twins has been proposed for more than two decades. With the progression of Industry 4.0, digital twin technologies have attracted increasing interest from researchers. It has been widely implemented across various industries for solving problem like condition monitoring, fault diagnosis, remaining useful life prediction, performance and maintenance strategy optimization, decision making, etc. Given this variety, each digital twin may have unique purposes and applications and can vary in complexity. However, the current literature lacks a comprehensive classification model for digital twins in engineering asset management applications. This paper offers a comprehensive review of the current state and development of digital twin technology, beginning with a detailed introduction that covers its origins and technological evolution. It introduces a novel classification method that categorizes digital twins based on their capabilities and purposes, helping to systematically understand their diverse functions and applications. By integrating current knowledge with anticipated advancements, this article contributes significantly to the literature, proposing a roadmap for the future development of digital twins, with a particular focus on their application in monitoring conditions, diagnosing faults, and predicting failures in complex systems.
KW - Artificial intelligence
KW - Asset management
KW - Condition monitoring
KW - Digital twin
KW - Industry 4.0
KW - Predictive maintenance
UR - https://www.scopus.com/pages/publications/105028280024
UR - https://link.springer.com/book/10.1007/978-3-032-00968-5
U2 - 10.1007/978-3-032-00968-5_40
DO - 10.1007/978-3-032-00968-5_40
M3 - Conference contribution
AN - SCOPUS:105028280024
SN - 9783032009678
SN - 9783032009708
VL - 1
T3 - Mechanisms and Machine Science
SP - 471
EP - 481
BT - Proceedings of the UNIfied Conference of DAMAS, IncoME and TEPEN Conferences (UNIfied 2025)
A2 - Wei, Kexiang
A2 - Yang, Wenxian
A2 - Dai, Juchuan
A2 - Chen, Bingyan
PB - Springer, Cham
Y2 - 16 May 2025 through 19 May 2025
ER -