Circular Manufacturing 5.0
Revolutionizing Photovolatic Production
Human-Centred AI-aided Digital Framework for Closed-Loop Photovoltaic (PV) products Value Chains
PROJECT OVERVIEW
Circular Manufacturing 5.0
CIRCMAN5.0 is an initiative aimed at transforming the photovoltaic (PV) manufacturing sector into a more sustainable and efficient industry through the use of circular manufacturing principles. This project focuses on developing a human-centered, AI-aided digital framework designed to optimize the entire lifecycle of PV products—from design and production to end-of-life recovery. By integrating cutting-edge technologies such as machine learning, digital twins, and blockchain, CIRCMAN5.0 seeks to reduce environmental impact, enhance resource efficiency, and foster a sustainable future.
9
European Countries
19
High-profile European Partners
4
Use Cases
7
Research Centers
Technological Pillars
Technological Synergy for Industry Advancement
CIRCMAN5.0 leverages cutting-edge tools like AI, blockchain, and digital twins to enhance operational efficiency, improve transparency, and drive innovation in the photovoltaic sector.
AI-Driven Eco-Design and Simulation
CIRCMAN5.0 leverages AI-driven modeling and parametric simulation techniques to integrate circular-by-design principles. This eco-design approach ensures compliance with the latest EU regulatory standards while fostering sustainable product development.
Machine Learning-Powered Dynamic Manufacturing Optimization
Our ML-assisted algorithms enable real-time production reconfiguration, adapting to evolving conditions and optimizing manufacturing processes to reduce material waste and improve efficiency.
Cognitive Digital Twin Simulation
By adopting standardized Asset Administration Shell (AAS) protocols, our Cognitive Digital Twin technology enhances manufacturing process modeling with built-in cybersecurity-as-a-service functionalities. This ensures thorough, adaptable, and highly efficient manufacturing strategies for resource and waste management.
Circularity & Life Cycle Assessment (LCA) Framework
We integrate AI-based forecasting models, routing optimization techniques, and embodied energy and carbon emissions assessments to deliver a comprehensive evaluation of sustainability. This framework empowers manufacturers to make data-driven decisions for reducing environmental impact.
Human-in-the-Loop (HITL) Decision Support System
CIRCMAN5.0’s HITL Recommendation Engine provides actionable insights to optimize raw material usage, maximize material reuse, and implement End-of-Life (EoL) recycling strategies. This ensures prolonged product lifespans and enhanced sustainability.
Digital Product/Material Passport (DPP) & Distributed Ledger Technology
With DPP enabled by Distributed Ledger Technologies, CIRCMAN5.0 fosters circular matching of supply and demand for products and materials. Our Collaborative Space enhances transparency, traceability, and seamless information sharing across the value chain.
Sustainability
Measurable Impact for a Greener Future
CIRCMAN5.0’s success is defined through fine-grained Key Performance Indicators (KPIs) that track
By merging advanced digital technologies with sustainable manufacturing practices, CIRCMAN5.0 is leading the transition towards a circular, efficient, and environmentally conscious PV industry. Join us in shaping the future of sustainable energy!
Waste Reduction
Minimizing waste generation at every stage of production.
Material Transparency & Validation
Ensuring traceability and authenticity of materials.
Energy Efficiency
Lowering overall energy consumption.
Productivity Gains
Enhancing operational efficiency across the value chain.
Real-World Applications for Maximum Efficiency
Use Cases
Sustainable Design and Circular Production Strategies for PV Solar Panels
Sunage, Switzerland
Optimizing End-of-Life Recovery for Multi-PV Solar Panel Types
SoliTek, Lithuania
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University of Applied Sciences and Arts of Southern Switzerland SUPSI – CIRCMAN5.0 Partner
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Trust and Worth
Our Partners
CIRCMAN5.0 has received funding from the EU Horizon Europe research and innovation programme CL4-2024-TWIN-TRANSITION-01-05 under grant agreement No.101178331.
This work has received funding form the Swiss State Secretariat for Education, Research and Innovation (SERI).