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3DAIQ
The 3DAIQ project is a collaborative research and innovation initiative focused on advancing automated quality inspection in industrial manufacturing through artificial intelligence.
Objectives
Co-funded under the IRISS call promoted by the SMACT Competence Center, 3DAIQ brings together Concept Reply, TEC Eurolab, Università di Padova, and Blue Tensor to develop an AI-driven software platform capable of identifying and characterizing structural defects in industrial components using 3D imaging technologies.
The core objectives of the 3DAIQ project are:
• Automated Defect Detection: Develop a software platform that can autonomously detect and classify internal and external defects in a wide range of industrial components, regardless of geometry or sector.
• Advanced 3D Inspection: Leverage industrial computed tomography and AI to build high-fidelity 3D representations of parts, enabling detailed analysis without physical alteration or destructive testing.
• Standardization and Scalability: Move beyond component-specific solutions to a scalable inspection framework applicable across diverse manufacturing processes and parts.
• Efficiency and Operator Support: Reduce inspection time, improve accuracy, and enhance the working conditions of quality assurance teams through intelligent automation and intuitive user interfaces.
• Collaborative Innovation: Foster cross-disciplinary research and development by integrating expertise in machine learning, materials analysis, and industrial IoT from project partners.
Impact
The 3DAIQ project delivers significant technological and industrial impact:
Improved Manufacturing Quality: By automating defect recognition with AI, 3DAIQ enables faster and more reliable quality control, reducing the risk of defective products reaching end customers.
Enhanced Competitiveness: Manufacturers adopting the 3DAIQ platform can achieve higher throughput and lower inspection costs while ensuring consistent product standards, strengthening competitiveness in global markets.
Innovation in Inspection Technology: The integration of deep learning with 3D imaging and additive manufacturing for training data represents a significant step forward in non-destructive testing methods.
Cross-Sector Applicability: The flexible architecture and broad applicability of the software mean that firms across automotive, aerospace, energy, and other sectors can benefit from automated anomaly detection.
Sustainability and Efficiency: By reducing manual inspection effort, lowering scrap rates, and accelerating decision cycles, 3DAIQ contributes to more sustainable production workflows and better resource utilization.
Project Info
3DAIQ develops an AI-driven software platform capable of identifying and characterizing structural defects in industrial components using 3D imaging technologies. The solution harnesses a combination of industrial computed tomography (iCT), Additive Manufacturing, advanced deep learning algorithms, and IoT integration to transform how product quality is assessed across manufacturing sectors.
The project 3DAIQ - CUP H99J24000040004 was funded by SMACT through the BANDO PROGETTI IRISS (Innovazione, Ricerca Industriale e Sviluppo Sperimentale) 2023, within PNRR - Next Gen. EU - M4C2I2.3.