MEDUSA

MEDUSA - Manufacturing as a service framework decentralized secure data exchange promoting sustainability and circularity

Project Description

Medusa Maas: Enabling Manufacturing as a Service through secure data exchange, AI-driven efficiency, and equal access to on-demand manufacturing services across Europe, challenging the dominance of large corporations by democratizing access to production capabilities for all businesses.

MEDUSA framework will facilitate the access to manufacturing capabilities by integrating MaaS B2B marketplaces across industries and providing AI-driven services to support outsourcing, remanufacturing decisions, plant reconfiguration, production monitoring, and sustainable, circular, and transparent manufacturing, in line with EC guidelines for trustworthy AI. The ambitions outlined above will be realized through the MEDUSA framework, which relies on five technological pillars.

In essence, the project will deliver:

• Manufacturing as a Service Decision Support Platform: The MEDUSA framework offers a decision support platform for outsourcing production, integrating AI, data, and visualization tools, utilizing a low-code web interface for efficient production chain setup.
• Automation engineering platform for Manufacturing Assets based on real-time IEC 61499 and Edge-Cloud Computing: The Automation Layer (OT) virtualizes physical production assets to interface with IT systems like AI and digital twins, using the IEC 61499 standard for flexible, secure computing.
• Multi-ontology methodology: MEDUSA integrates Semantic Web technologies and multi-ontology knowledge graph for seamless information sharing, modeling production assets and security provisions, generating adaptation plans, and recognizing security threats.
• Secure, decentralized and traceable data exchange: MEDUSA’s decentralized data exchange method utilizes IPFS for P2P file sharing, Blockchain for secure storage, and NoSQL databases for scalability, ensuring privacy and transparency.
• AI tools: Our algorithms improve sustainable production by matching customers with optimal providers, estimating production parameters using Digital Twins, ensuring energy efficiency, simplifying terminology, and tracking sustainability impacts.