MetaD-DT: A Reference Architecture Enabling Digital Twin Development for Complex Engineering Equipment
Digital twin technology is emerging as a critical enabler for the lifecycle management of complex engineering equipment, yet its implementation faces significant hurdles. Generic, one-size-fits-all digital twin platforms often fail to address the unique characteristics of this domain—such as tightly coupled multi-physics, high-fidelity modeling requirements, and the need for real-time model execution under harsh operating conditions. This creates a critical need for a structured, reusable blueprint. However, a dedicated reference architecture that systematically guides the development of such specialized digital twins is notably absent. To bridge this gap, this paper proposes MetaD-DT, a reference architecture designed to enable and streamline the development of digital twins specifically for complex engineering equipment. We detail its comprehensive four-layer architecture, core functional modules, and streamlined graphical development workflow. The MetaD-DT’s efficacy and practical value are validated through two distinct industrial case studies: a health management system for diesel engine Diesel Particulate Filter (DPF) and an intelligent control optimization system for Indirect Air-Cooled (IAC) towers. These applications validate the framework’s ability to support the creation of robust digital twins that can effectively handle complex industrial dynamics and improve O&M (Operation And Maintenance) efficiency. This work provides a systematic architectural blueprint for the future development of specialized and efficient digital twins in the engineering equipment domain.
Authors
- Feng Wang (ORCID: https://orcid.org/0000-0003-1221-7242)
- Yi Gu
- Hanyu Gao
- Taoping Zhao
Institutions
- Zhejiang University of Science and Technology (CN)
- Zhejiang University (CN)
- Wuxi Institute of Technology (CN)
Publication Details
- Journal
- Electronics
- Published
- 2025-12-22
- DOI
- https://doi.org/10.3390/electronics15010038
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China