Technology
AUTO-TWIN addresses the technological shortcomings and economic liability of the current system-engineering model
Automated digital twin generation, operations, and maintenance in circular value chains
AUTO-TWIN will provide the digital tools to create and execute a responsive information system for real time control of material flows in circular economies based on digital value chain representations.
The AI-enable digital twins will support technicians and operators to make optimal decisions concerning repair, refurbishing, recycling, and reuse of products.
Automatically Generated & Autonomous Digital Twins
AUTO-TWIN will develop a novel data-driven method based on a process mining approach for generation and adaptation of multi-fidelity resolution digital twins from data acquired, at multiple levels, along the value chain. Full automation, trustworthiness, and “skill-free” play are key points of the approach.
2. A Trustworthy high-resolution track & trace of products and processes among different actors in circular value chains.
Circular Data Space
An IDS-based data space to promote and facilitate the collection, ownership, and secure exchange of manufacturing / product / business data within value-networks. Will enable trust in the whole (re)manufacturing and logistic processes among actors sharing their business related data in the circular value chain.
Digital Product Passport
All the technologies and solutions that enable high-resolution track and tracing providing digital object lifecycle management as well as the product/process information that users across the circular value chain require. Will be the fundamental element to enable effective and customised decisions for recycling, re- manufacturing, refurbishing, and reuse of manufactured products and components.
Circular Digital Thread
A set of AI-features based on blockchain technologies for trust tracking and tracing of items. Will help to determine the current and past locations (and other information) of unique components and products as well as predict their future location through integration with digital twin predictions.
3. Reduce skills and knowledge gaps for all involved actors through augmented intelligence
Situation Aware Data Enrichment & Explainability Techniques
A set of explainable-based features to facilitate human-machine cooperation and guidance. This will consider process casual sequencing and constraints, broader context information (e.g., temporal) behind decisions, inferential association between subsequent process enactments
Reducing skills and knowledge gap and empowering humans through AI
AUTO-TWIN will “reduce the skills and knowledge gap for the actors involved” along several dimensions.
1. It will define the approach for automatically generating digital twins of circular economies without the need of high skills on digital model development.
2. It will improve the level of skills and knowledge of workers through profiling tools, suggesting actions to cover the gap among the expected level of competences.
3. All the outputs from process mining algorithms, AI tools, and optimisation methods will be elaborated and compliant with Situation Aware and Situation Explainability principles.
4. Augmented intelligence algorithms for decision making at Green Gateways
Digital Services for Operations of Green Gateways
A set of AI, process mining, and optimisation algorithms implemented into digital tools to support decision making of actors operating at Green Gateways. Will help actors along the value chain to leverage the green technologies by optimally synchronising flows along the circular value chain at recycling, re-manufacturing, refurbishing, and reuse gateways and by suggesting the right pricing for the new, re-manufactured and refurbished products
The easy connection with the Common Data Space and the AUTO-TWIN Platform will make possible the developed AI, process mining, and optimisation algorithms to consider and handle real-time production data.
Specific Focus Areas
Material saving, repair, refurbishing, re-manufacturing, recycling, and reuse of products and components.