Digital Twins for Smart Industrial Systems
Modern industrial systems benefit from using digital support tools to strengthen both short- and long-term decision-making capabilities. In the past decade, the Digital Twin (DT) has rapidly emerged as one of the most prominent technologies of this era and has caught the attention of the industry, academia, and governments. DTs represent the digital counterpart of a production system in the physical world. The physical and virtual parts interact with each other to provide useful services to the users. Thus, the DT connection with existing information systems is an essential element for their development. This track aims to unveil the novelty brought by DTs for an efficient and sustainable production. Contributions to the track should explore DT applications, modelling approaches, lifecycle assessment methodologies, as well as methods and tools to support the DT integration with information systems of different natures.
Topics of the track include, but are not limited to:
- Digital Twin architectures and implementation methodologies for smart manufacturing systems.
- Data models and advanced data analytics tools for Digital Twins.
- Data security for Digital Twins.
- Smart interfaces and connectors to information systems.
- MES-integrated Digital Twins.
- Software architectures for next-generation Manufacturing Execution Systems (MES).
- Artificial Intelligence (AI) for Digital Twin Design and Operations.
- Simulation-based Digital Twins (e.g., Discrete Event Simulation).
- Digital Twins for sustainability and energy-efficient manufacturing.
- Digital Twins for ramp-up and improvement of manufacturing systems.
- Digital Twins for production planning, scheduling, and control.
- Digital Twins for maintenance, repair, diagnostics, and prognostics.
- Digital Twins for reliability and safety of manufacturing assets or systems.
- Digital Twins for robust and resilient manufacturing.
- Digital Twins for Life Cycle Assessment of manufacturing systems.
- Methods and Tools for Automated Generation of Digital Twins.
- Case studies and industrial applications of Digital Twins.
- Development of Digital Twins into data spaces, connected data ecosystems, and the industrial metaverse.
Track Chair:
- Prof. Giovanni Lugaresi (KU Leuven, Belgium), e-mail: giovanni.lugaresi@kuleuven.be
Track Co-chairs:
- Dr. Hendrik van der Valk (TU Dortmund, Germany), e-mail: hendrik.van-der-valk@tu-dortmund.de
- Dr. Edward Hua (The MITRE Corporation), e-mail: ehua@mitre.org