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Inline-Acquired Product Point Clouds for Non-Destructive Testing: A Case Study of a Steel Part Manufacturer

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Publicado en:Machines vol. 13, no. 2 (2025), p. 88
Autor Principal: Ntoulmperis, Michalis
Outros autores: Discepolo, Silvia, Castellini, Paolo, Catti, Paolo, Nikolakis, Nikolaos, van de Kamp, Wilhelm, Alexopoulos, Kosmas
Publicado:
MDPI AG
Materias:
Nondestructive testing
Inspection
Quality control
Artificial intelligence
Scanners
Lasers
Sensors
Triangulation
Robots
Algorithms
Manufacturers
Methods
Computer aided design > CAD
Manufacturing
Uncertainty analysis
Dimensional analysis
Vision systems
Case studies
Steel products
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Resumo:Modern vision-based inspection systems are inherently limited by their two-dimensional nature, particularly when inspecting complex product geometries. These systems are often unable to capture critical depth information, leading to challenges in accurately measuring features such as holes, edges, and surfaces with irregular curvature. To address these shortcomings, this study introduces an approach that leverages computer-aided design-oriented three-dimensional point clouds, captured via a laser line triangulation sensor mounted onto a motorized linear guide. This setup facilitates precise surface scanning, extracting complex geometrical features, which are subsequently processed through an AI-based analytical component. Dimensional properties, such as radii and inter-feature distances, are computed using a combination of K-nearest neighbors and least-squares circle fitting algorithms. This approach is validated in the context of steel part manufacturing, where traditional 2D vision-based systems often struggle due to the material’s reflectivity and complex geometries. This system achieves an average accuracy of 95.78% across three different product types, demonstrating robustness and adaptability to varying geometrical configurations. An uncertainty analysis confirms that the measurement deviations remain within acceptable limits, supporting the system’s potential for improving quality control in industrial environments. Thus, the proposed approach may offer a reliable, non-destructive inline testing solution, with the potential to enhance manufacturing efficiency.
ISSN:2075-1702
DOI:10.3390/machines13020088
Fonte:Engineering Database