3D X-Ray Computed Tomography

The project aims to establish an X-ray Computed Tomography laboratory for industrial applications (XCT-Lab) equipped with both a high-resolution CT scanner for off-line, sample-based inspection and an in-line X-ray tomograph capable of acquiring three-dimensional images directly within production processes. Although the in-line system will operate at lower spatial resolution, it will enable acquisition speeds compatible with industrial manufacturing cycles.

Research

By deeply integrating machine vision, numerical simulation and physics-informed machine learning methods, the project aims at lay the foundations for next-generation CT-based in-line quality control of plastic, steel, and metal alloy components.

The proposed framework is designed to enable automated defect detection from 3D in-line data and the prediction of their impact on component performance through combined simulation-driven and data-driven models.

The laboratory will also develop large-scale benchmarking datasets for industrial CT and promote methodological advances through international scientific challenges and competitions.

People

Laboratory Head: Oswald Lanz

Co-Investigator: Franco Concli

Team: Andrea Cittadini, Vedang Nadkarni, Artem Merinov

Collaborators: Alessandro Torcinovich (ETH Zurich), Alessandro Bombini (INFN Florence)

Funding

Program: ERDF 2021-2027

Priority: 3rd Call, Priority 1 “SMART”, Action 2

Duration: 01.01.2026 – 31.12.2028