Welcome the official start of AUTO-TWIN “Data-driven method based on a process mining approach for Automated Digital Twin generation, operations, and maintenance in circular value chains” (GA n. 101092021), a winning and pioneering project for the recent Horizon Europe call “Digital tools to support the engineering of a Circular Economy”.
The AUTO-TWIN project aims to revolutionize the current system engineering model by introducing a new automated process-aware discovery method to create trustworthy digital twins. The project is aimed at supporting circular economies and will showcase its solutions in three distinct value chains: battery refabrication, plastic recycling, and medical device sterilization.
The first objective of the project is to automate the creation, management, and upkeep of digital twins in circular value chains through the development of a data-driven process-mining method. The focus is on full automation, trustworthiness, and ease of use without any need for specialized skills.
The second objective is to establish a common data space for secure and trustworthy data exchange between stakeholders in value chains. The aim is to bridge the information gap that impedes the growth of circular economies in Europe by defining, testing, and implementing systems and solutions in real-world business environments.
The third objective is to reduce the skill and knowledge gap through augmented intelligence. The project is working towards creating a reliable, complete, and standardized framework for assessing skills and mapping production processes. The goal is to use explainable AI techniques to lower the skill requirement, tools to evaluate the skills of workers in a specific context, and a data-driven approach to determine the most efficient upskilling path.
The fourth objective is to enhance rapid decision-making at Green Gateways by using augmented intelligence algorithms. The project aims to analyze correlations and transform them into knowledge to support decision-making at Green Gateways, using digital twin predictions and knowledge to optimize value chain coordination under changing conditions.
AUTO-TWIN represents a new and innovative method for creating digital twins, digital replicas of physical systems, by adopting an International Data Space (IDS) based common data space to automate the digital twin creation process, making it more cost-effective and efficient. The project also integrates advanced hardware technologies into the digital thread to create smart Green Gateways, enabling companies to make data and digital twin-based green decisions.
The Team of researchers from the Department of Mechanical Engineering will utilize their expertise in process mining for manufacturing systems to create algorithms for enhancing the digital twin's component models and to create functional modules for converting graph models into discrete event simulation models and for validating results in real-time. A significant contribution will also be related to the improvement of the knowledge graph model using conformance checking results and to develop multi-criteria optimization methods.
Professor Andrea Matta, affiliated with the Department of Mechanical Engineering in Politecnico di Milano, will take the lead in managing the project, making sure it is completed on time and within budget. A strong consortium of 11 beneficiaries from Italy, Lithuania, Greece, Spain, Israel, and Turkey and 2 associated partners from Switzerland will work together for this three-year project and the 7.3 million€ total funding will provide our researchers the instruments to tackle some of the most critical challenges the world is facing in the upcoming years.