Imagine your factory had a digital twin that didn't just mirror the machines, but could actually think and predict problems before they happen. It connects different companies in a supply chain like a giant, secure digital map so everyone stays in sync. When a disruption hits, the system automatically suggests the best way to keep production moving while staying green.
Manufacturing ecosystems struggle with supply chain disruptions and unpredictable demands, leading to inefficiency and lack of resilience. There is a critical need for real-time, cross-organizational data sharing and adaptive decision-making to maintain production.
A four-layer MaaS platform featuring a decentralized knowledge graph, cognitive digital twins, a multi-objective decision support system, and a circularity assessment module.
If you are an aircraft component manufacturer dealing with unpredictable supply chain disruptions — this project developed a cognitive digital twin and decision support system that helps anticipate risks and optimize production across multiple goals.
If you are a circuit board producer dealing with volatile market demands — this project developed a decentralized knowledge graph and MaaS platform that ensures real-time data integration across organizations to maintain reliability.
If you are an industrial remanufacturing firm dealing with strict EU sustainability reporting — this project developed a circularity assessment module aligned with EU Digital Product Passport standards to improve traceability.
Based on available project data, no specific pricing or cost details are provided as this is a research and innovation action.
The project aims to evolve technologies from TRL3 to TRL6 across 2 use cases in the aerospace and electronics sectors, indicating a move toward industrial piloting.
Based on available project data, specific IP and licensing terms are not mentioned, though the project uses standard-based ontologies and blockchain for secure data integration.
Yes, the platform includes a circularity assessment module specifically aligned with EU Digital Product Passport (EU-DPP) standards.
It uses a Decentralized Knowledge Graph and standard-based ontologies to ensure seamless cross-organization data integration.
The consortium is heavily industry-driven, with 8 industrial partners (57% ratio) and 7 SMEs across 11 countries. This strong private-sector presence, combined with 3 universities and 2 research centers, suggests a high focus on practical application and commercial viability rather than pure academic research.
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