CARTIF Projects
ORGANIC
Biological transformation of additive manufacturing processes for the sustainable manufacturing of bio-inspired products
Description
ORGANIC aims to lead the biological transformation of additive manufacturing (AM) processes by integrating nature-inspired structural design, bio-intelligent technologies, and the use of fully recyclable biomaterials in Fused Granulate Fabrication (FGF). An integrated optimization tool based on process-structure-property-performance (PSPP) relationships, high-precision digitized FGF equipment, and a cognitive control system with self-configuration, self-monitoring, self-optimization, and self-repair capabilities will be developed. Furthermore, an AI-based “gentle intelligence” system will enable the continuous evolution of the manufacturing process, ensuring sustainable and efficient production. Ultimately, the project will validate these technologies by manufacturing a demonstrator of optimized and fully recyclable offshore wind turbine blade components.
Objectives
- Gentellignent Additive Manufacturing (AM) Framework. Gentellignence links design, production, and quality data through semantic digital twins and AI-powered knowledge graphs, enabling self-adaptive, zero-defect, and sustainable production. From right-first-time manufacturing to bio-inspired materials, it drives smarter, more flexible, and future-ready factories.
- Open CAx: Bio-inspired Lattice Structure Optimization. A single, integrated workflow linking design, toolpath, and process planning enables the efficient creation of bio-inspired lattice structures. This approach improves structural performance while reducing weight and material usage, resulting in strong, lightweight, and sustainable components. AI-powered tools predict material behavior and performance, providing precise control over every parameter to ensure all designs perform as intended.
- Advanced FGF Printing for Bio-Based Composites. A large-format fusion granule (FGF) manufacturing system will enable the production of high-performance components from bio-based materials. Precisely controlled extrusion, real-time monitoring, and advanced thermal management deliver strong, lightweight, and sustainable parts optimized at the fiber level.
- Self-X AM Control. Traditional Additive Manufacturing (AM) struggles with real-time variations, often leading to defects, especially with bio-based materials. We are poised to change this with a Self-X adaptive control system that predicts, optimizes, and corrects in real time. Its AI-powered self-monitoring and self-healing framework ensures greater reliability, repeatability, and quality, transforming the complex printing of bio-composites while simultaneously increasing efficiency and sustainability.
- Large-scale, biology-inspired manufacturing. Building complex, biology-inspired structures on a large scale presents a significant challenge for additive manufacturing. Material variability, process stability, and structural integrity often limit performance, especially for bio-based composites. We address this challenge by combining advanced fiber-reinforced materials, self-adaptive additive manufacturing systems, and AI-driven design optimization.
Actions
-
- Development of a cognitive control system for the FGF process, based on deep learning and real-time optimization.
- Design and implementation of the biointelligent control architecture, integrating self-X capabilities (self-configuration, self-monitoring, self-optimization, and self-repair).
- Integration of the control system with the project’s AAS digital platform/digital twin, ensuring real-time communication and interoperability with the system’s sensors and actuators.
- Experimental validation and tuning of the biointelligent control algorithms in AIMEN’s FGF demonstrator, guaranteeing the autonomous and sustainable performance of the printing process.
Expected results
- Cognitive control system for operational FGF, capable of optimizing printing parameters in real time using artificial intelligence and reinforcement learning for an AM system.
- Exploitable result of the OER2 project: Real-time self-X control strategies.
R&D Line
- Optimization of operations management in manufacturing.
Partners
Horizon Europe
101178127
Total Budget: 4,994,822.50€
CARTIF Budget: 430,906.25€
CARTIF Funding: 430,906.25€
Duration: 01/06/2025 – 30/11/2028
Responsible
Daniel Gómez Martín
Industrial and Digital Systems Division
Networking
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