Generally speaking, a digital twin is a virtual representation that serves as the virtual counterpart of a physical entity with real-time synchronization between the physical and the virtual parts. In particular, digital twins aggregate data generated in the physical world, enable experimenting with this data in the simulations of assets, and provide insights that may be deployed back to the physical world.
Digital twins are increasingly being developed in multiple domains and have the potential to impact industry and society in different ways. They are considered to be the core of the Industrial Internet of Things as well as the next generation of cyber-physical systems. In particular, they have been identified as the top priority emerging technology by the IEC and the ISO Joint Technical Committee and as the top trend for driving digital innovation by Gartner.
However, the application of digital twins is not limited to industrial domains; they are also capable of exploring and defining the most effective interventions for large businesses and societal systems to achieve their operational, economic, and sustainability-related objectives (e.g., Gemini principles).
Despite this potential, fundamental methodological and technical challenges remain, motivating academic research and collaboration between industry and academia.
The 3rd International Workshop on Digital Twin Architecture (TwinArch) and Digital Twin Engineering (DTE) will provide researchers and practitioners with a unique forum to exchange ideas and experiences in the field of digital twins from the perspective of software architecture and systems and software modeling.
Topics of interest include, but are not limited to:
Software Architecture Description for and with Digital Twins:
- Architectures of digital twins, including digital threads and digital shadows
- Architectures for cyber-physical systems with digital twins
- Integration of multiple stakeholders’ concerns into the software architecting process of digital twins
- AI in the architecture of digital twins, e.g., AI for generating simulation models for digital twins
- Case studies involving simulations to guide the development of system architecture
From Software Architecture Models to Executable Simulation Models:
- (Semi-)formal approaches supporting architecture models with digital twins at design time / run time
- Approaches for (semi-)automatically creating simulation models from architecture
- Architecture frameworks for the development of digital twin architectures from multiple viewpoints
- Case studies involving simulations to guide systems architecture development.
Digital Twins for Adaptive Systems / Software Architectures:
- Software architecture practices to support adaptations
- AI technologies for adaptation (e.g., case-based-reasoning, reinforcement learning)
- Cognitive digital twins
- Case studies of adaptive architectures
Digital Twins and Continuous Engineering Practices:
- Runtime verification of systems with digital twins
- Monitoring the quality of systems using digital twins
- Self-validation of digital twins
- Case studies of continuous engineering using digital twins
Models, Methods, and Techniques for Developing Digital Twins
- Requirements engineering for digital twins
- Conceptual modelling for socio-techno-economical systems
- Knowledge management for capturing domain knowledge
- Methods and models for capturing the inherent uncertainty of business and societal systems
- Simulation of business and social systems
- Multi-paradigm modelling and co-simulation techniques
- Validation and verification of digital twins
Technology and its Applications
- Application of enterprise modelling techniques for digital twin initiatives from different domains
- Relevance of AI and optimization techniques
Aspects and Domains of Interest
- Industry 4.0
- Supply chain management
- Social systems for policy making, urban planning, and healthcare;
- Sustainability
- Smart cities
Fraunhofer Institute for Experimental Software Engineering IESE