Digital Twin Reliability

Aims & Scope

Digital Twin has been considered as a newly emerging technology that benefits the development of many research areas and disciplines. Driven by requirements from the Physics-of-Failure and machine-learning based reliability design and analysis methods, high precise predictions of the failures under dynamical uncertain conditions become the key concern in the synergistic design of products between their reliability and functional performance. This gives birth to a novel multi-disciplinary research area “Reliability Digital Twin (RDT)”, which should be able to fully utilize the multidimensional data collected from the products, including product model data, statistical data of fault events, real-time operational status data, historically environment and load data, etc., to provide more accurate simulation and reliability predictions, by using the Digital Twin technologies. And the related new ideas and solutions have been emerged all over the world in the recent years. To this end, this session is arranged for presenting these innovative researches from both theoretical and application perspectives to academic and engineering circles.

Submissions that reflect the session scope and current state of the field are welcome in areas including but not limited to:

▪ Methodologies and application of combing reliability and digital twin

▪ Development of RDT of products in its design and maintenance stages  

▪ AI and LLM for RDT

▪ Uncertainty analysis in RDT

▪ Advanced application researches of RDT

▪ Intelligent predictive maintenance using RDT

▪ PHM on embodied intelligence devices using RDT

▪ PHM on swarm intelligent systems using RDT