Inline-Acquired Product Point Clouds for Non-Destructive Testing: A Case Study of a Steel Part Manufacturer
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| Udgivet i: | Machines vol. 13, no. 2 (2025), p. 88 |
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| Hovedforfatter: | |
| Andre forfattere: | , , , , , |
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MDPI AG
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| Online adgang: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2075-1702 | ||
| 024 | 7 | |a 10.3390/machines13020088 |2 doi | |
| 035 | |a 3171132320 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231531 |2 nlm | ||
| 100 | 1 | |a Ntoulmperis, Michalis |u Laboratory for Manufacturing Systems & Automation (LMS), Department of Mechanical Engineering & Aeronautics, University of Patras, Rio, 26504 Patras, Greece | |
| 245 | 1 | |a Inline-Acquired Product Point Clouds for Non-Destructive Testing: A Case Study of a Steel Part Manufacturer | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article Case Study | ||
| 520 | 3 | |a 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. | |
| 653 | |a Nondestructive testing | ||
| 653 | |a Inspection | ||
| 653 | |a Quality control | ||
| 653 | |a Artificial intelligence | ||
| 653 | |a Scanners | ||
| 653 | |a Lasers | ||
| 653 | |a Sensors | ||
| 653 | |a Triangulation | ||
| 653 | |a Robots | ||
| 653 | |a Algorithms | ||
| 653 | |a Manufacturers | ||
| 653 | |a Methods | ||
| 653 | |a Computer aided design--CAD | ||
| 653 | |a Manufacturing | ||
| 653 | |a Uncertainty analysis | ||
| 653 | |a Dimensional analysis | ||
| 653 | |a Vision systems | ||
| 653 | |a Case studies | ||
| 653 | |a Steel products | ||
| 700 | 1 | |a Discepolo, Silvia |u Dip. di Ingegneria Industrial e Scienze Matematiche, Universita Politecnica delle Marche, Via Brecce Bianche 10, 60131 Ancona, Italy | |
| 700 | 1 | |a Castellini, Paolo |u Dip. di Ingegneria Industrial e Scienze Matematiche, Universita Politecnica delle Marche, Via Brecce Bianche 10, 60131 Ancona, Italy | |
| 700 | 1 | |a Catti, Paolo |u Laboratory for Manufacturing Systems & Automation (LMS), Department of Mechanical Engineering & Aeronautics, University of Patras, Rio, 26504 Patras, Greece | |
| 700 | 1 | |a Nikolakis, Nikolaos |u Laboratory for Manufacturing Systems & Automation (LMS), Department of Mechanical Engineering & Aeronautics, University of Patras, Rio, 26504 Patras, Greece | |
| 700 | 1 | |a van de Kamp, Wilhelm |u VDL WEWELER bv, 7325 WC Apeldoorn, The Netherlands | |
| 700 | 1 | |a Alexopoulos, Kosmas |u Laboratory for Manufacturing Systems & Automation (LMS), Department of Mechanical Engineering & Aeronautics, University of Patras, Rio, 26504 Patras, Greece | |
| 773 | 0 | |t Machines |g vol. 13, no. 2 (2025), p. 88 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3171132320/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3171132320/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3171132320/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |