PC3: TWINOPS

Overview

Current digital twins (DTs) utilize cutting-edge technologies such as IoT, 5G, Cloud, AI, and 3D modeling. However, DT development entails high costs and lengthy implementation times, underscoring the need for a new specialized methodology.

Engineering digital twins (EDT) involves multiple disciplines and relies on various technologies and research areas. This multidisciplinarity necessitates the definition of domain-specific languages (DSL) and specific viewpoints to be integrated into a coherent global architecture framework as defined in ISO42010.

Any complex system development must begin with good specification, and DT development is no exception. The project investigates the specificities of DT development to support their formal specification (e.g., how do you specify the expected level of precision of a digital twin?).

Conformity assessment of digital twins according to existing standards and regulations is essential to build user confidence in real-world DT deployment. This project explores the integration of AI and Model-Based Systems Engineering (MBSE) practices to automate conformity assessment activities.

DTs are complex systems, and their engineering field requires new tools that support tightening collaborative engineering to reduce costs and delays and improve quality. Concurrent and agile engineering and better knowledge sharing are necessary. The project also addresses integrating AI into engineering methodologies for DT and their Integrated Development Environment (Augmented-IDE), investigating human-bot inclusion and ensuring the Augmented IDE adapts to all users, regardless of their cognitive, economic, social, or cultural levels.

Integrating analysis tools and techniques early in the design phase, especially when using MBSE approaches, is crucial. This early analysis can improve decision-making, and “analysis-in-the-loop” can help assess the impacts of design choices on key performance indicators.

The growing importance of AI models integrated into DT requires intensive testing procedures. Testing machines using or “embedding” DTs is a critical question. New methods for verifying, validating, and qualifying uncertainties (VVUQ) will be proposed and integrated into a common methodology, supporting continuous integration and deployment.

The environmental impact of digital systems is a reality. DT design and operations need to be optimized to minimize their ecological footprint. The project develops frameworks to evaluate environmental footprint based on ADEME’s PCR for digital services, guiding eco-design decisions during the engineering phase.

Associated Use Cases

Use cases in PC3 focus on industrial applications where DT technology is crucial, involving multiple stakeholders and considering co-evolution of physical and digital twins, especially where safety is a concern. Connections with use cases where sustainability is key are also prioritized.

Investigator & Project Partners

Principal Investigator:

Jean-Michel Bruel

Professor, U. Toulouse Jean Jaurès

Jean-Michel Bruel is a full professor at the University of Toulouse. Its research includes the development of software-intensive Cyber-Physical Systems, as well as methods/model/language integration, with a focus on Requirements and Model-Based Systems Engineering. He has served as the Laboratory Representative for Toulouse 2 Jean Jaurès University from 2016 to 2020. He has been a member of the Strategic Research Committee of the IRIT CNRS laboratory since 2021. He has been the holder of the Chair of Model-Driven Systems Engineering between AIRBUS and Toulouse Jean Jaurès University since 2022, and joined the International Research Laboratory in AI in 2023. He is co-lead the GDR CNRS SciLog for the next 5 years.

Participating Partners:

Project Implementation

The project is structured into three interconnected work packages, addressing methodology, continuous engineering, collaborative tools, and sustainability.