3D scanner technology in the reverse engineering of complex mechanical components: A literature review
DOI:
https://doi.org/10.58712/jerel.v5i1.213Keywords:
3D scanning, geometric accuracy, modal analysis, reverse engineeringAbstract
This study addresses the challenges involved in the reverse engineering of complex mechanical components, where conventional manual measurement methods often produce geometric deviations that negatively affect the reliability of advanced engineering analyses. A descriptive literature review was conducted to evaluate the role of 3D scanning technology in overcoming these limitations. The study compares various data acquisition methods, including laser scanning, structured light scanning, and photogrammetry, while also analysing how the level of geometric accuracy influences finite element simulation results and structural analysis outcomes. The review found that 3D scanning significantly improves geometric fidelity compared with traditional techniques, thereby enhancing the validity of numerical simulations. However, the review also identified that the quality of the final model is highly dependent on the selected scanning technology, surface conditions, and advanced reconstruction processes such as point cloud registration and mesh generation. The findings indicate that although 3D scanning offers superior precision, geometric deviations may still occur and influence structural parameters. This study concludes that the integration of 3D scanning into reverse engineering workflows requires systematic validation to ensure not only visual accuracy but also functional reliability in engineering applications. Furthermore, this review highlights a critical research gap, suggesting that future studies should place greater emphasis on the direct correlation between geometric accuracy and engineering simulation outcomes.
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Abdalla, E., Panfiglio, S., Parisi, M., & Di Bella, G. (2026). A Review on Reverse Engineering for Sustainable Metal Manufacturing: From 3D Scans to Simulation-Ready Models. Applied Sciences, 16(3), 1229. https://doi.org/10.3390/app16031229
Alsoufi, M. S., Bawazeer, S. A., Alhazmi, M. W., Hijji, H. H., Alhazmi, H., & Alqurashi, H. F. (2025). Dimensional Accuracy and Measurement Variability in CNC-Turned Parts Using Digital Vernier Calipers and Coordinate Measuring Machines Across Five Materials. Materials, 18(12), 2728. https://doi.org/10.3390/ma18122728
Barry, E. S., Merkebu, J., & Varpio, L. (2022). State-of-the-art literature review methodology: A six-step approach for knowledge synthesis. Perspectives on Medical Education, 11(5). https://doi.org/10.1007/s40037-022-00725-9
Barsanti, S. G., Guagliano, M., & Rossi, A. (2022). 3D Reality-Based Survey and Retopology for Structural Analysis of Cultural Heritage. Sensors, 22(24), 9593. https://doi.org/10.3390/s22249593
Benrabah, A., Senent Domínguez, S., Carrera-Ramírez, F., Álvarez-Alonso, D., de Andrés-Herrero, M., & Jorda Bordehore, L. (2023). Structural and Geomechanical Analysis of Natural Caves and Rock Shelters: Comparison between Manual and Remote Sensing Discontinuity Data Gathering. Remote Sensing, 16(1), 72. https://doi.org/10.3390/rs16010072
Catbas, F. N., Cano, J. A., Luleci, F., Walters, L. C., & Michlowitz, R. (2023). On the Generation of Digital Data and Models from Point Clouds: Application to a Pedestrian Bridge Structure. Infrastructures, 9(1), 6. https://doi.org/10.3390/infrastructures9010006
Chlost, M., & Bazan, A. (2025). Comparison of Methods for Reconstructing Irregular Surfaces from Point Clouds of Digital Terrain Models in Developing a Computer-Aided Design Model for Rapid Prototyping Technology. Designs, 9(4), 81. https://doi.org/10.3390/designs9040081
Cuesta, E., Meana, V., Álvarez, B. J., Giganto, S., & Martínez-Pellitero, S. (2022). Metrology Benchmarking of 3D Scanning Sensors Using a Ceramic GD&T-Based Artefact. Sensors, 22(22), 8596. https://doi.org/10.3390/s22228596
Debnath, B., Pourfarash, Z., Ghorpade, B., & Raman, S. (2025). Integrating Reverse Engineering for Digital Model Reconstruction and Remanufacturing of Mechanical Components: A Systematic Review. Metrology, 5(4), 66. https://doi.org/10.3390/metrology5040066
Fontana, R., Gambino, M. C., Greco, M., Pampaloni, E., Pezzati, L., & Scopigno, R. (2003). High-resolution 3D digital models of artworks. In R. Salimbeni (Ed.), Optical Metrology for Arts and Multimedia (pp. 34–43). https://doi.org/10.1117/12.501248
Freni, F., Panfiglio, S., Abdalla, E., Cannuli, A., Di Bella, G., & Montanini, R. (2026). A Quantitative Method for 3D Scan Quality Assessment Under Different Surface Conditions for Reverse Engineering of Shipyard Components. Sensors, 26(5), 1581. https://doi.org/10.3390/s26051581
Ghorbani, H., & Khameneifar, F. (2025). Denoising and Simplification of 3D Scan Data of Damaged Aero-Engine Blades for Accurate and Efficient Rigid and Non-Rigid Registration. Sensors, 25(19), 6148. https://doi.org/10.3390/s25196148
Jang, A., Ju, Y. K., & Park, M. J. (2022). Structural Stability Evaluation of Existing Buildings by Reverse Engineering with 3D Laser Scanner. Remote Sensing, 14(10), 2325. https://doi.org/10.3390/rs14102325
Kandiyil, D. R., Sadique, M., Lee, D., Amoako-Attah, J., & Al Mufti, R. (2025). The Role of Embodied Carbon in Sustainable Construction: A Review of Qatar’s Practices and Perspectives. ASME Journal of Engineering for Sustainable Buildings and Cities, 6(1). https://doi.org/10.1115/1.4067896
Konecki, K., Wojtkowiak, D., & Tala?ka, K. (2024). Evaluating the Accuracy of the Reverse Engineering Process of Worn, Non-Standard Spur Gears—Pilot Studies. Applied Sciences, 14(14), 6090. https://doi.org/10.3390/app14146090
Lakovaki, E., Konstantakis, M., Giaourtsakis, I., Rentoumi, E., Protopapas, D., Psarras, C., & Koskeridou, E. (2026). When Reality Meets Practice: Challenges and Pitfalls in 3D Digitization Using Structured Light Scanning and Photogrammetry in Cultural Heritage. Information, 17(3), 237. https://doi.org/10.3390/info17030237
Lengvarský, P., Hagara, M., Hagarová, L., & Brian?in, J. (2025). Finite Element Model Updating of Axisymmetric Structures. Applied Sciences, 15(21), 11407. https://doi.org/10.3390/app152111407
Liu, Q., Cho, J., Bansal, M., & Niethammer, M. (2024). Rethinking Interactive Image Segmentation with Low Latency, High Quality, and Diverse Prompts. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 3773–3782. https://doi.org/10.1109/CVPR52733.2024.00362
Liu, Y., Obukhov, A., Wegner, J. D., & Schindler, K. (2024). Point2CAD: Reverse Engineering CAD Models from 3D Point Clouds. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 3763–3772. https://doi.org/10.1109/CVPR52733.2024.00361
Meana, V., Zapico, P., Cuesta, E., Giganto, S., & Martinez-Pellitero, S. (2024). Laser Triangulation Sensors Performance in Scanning Different Materials and Finishes. Sensors, 24(8), 2410. https://doi.org/10.3390/s24082410
Mhadgut, D. H., Phoenix, A., Kenyon, S. P., & Black, J. (2025). Modal Analysis of Self-Deployable Tape Spring Booms: A Reverse Engineering Approach. Journal of Vibration and Acoustics, 147(5). https://doi.org/10.1115/1.4068812
Nazim, A., Kondrát, M., Zidek, K., & Pitel, J. (2025). Methodology of Object Reconstruction by Photogrammetry and Structured-Light Scanning for Industrial 3D Visualisation. Sensors, 25(23), 7177. https://doi.org/10.3390/s25237177
Onyia, T. M., Olarinoye, I. A. A., & Jimoh, S. A. (2025). Advancements and Challenges in 3D Scanning: A Comprehensive Review of Engineering Applications. African Journal of Advances in Science and Technology Research, 18(1), 191–206. https://doi.org/10.62154/AJASTR.2025.018.010640
Turek, P., Bez?ada, W., Cierpisz, K., Dubiel, K., Frydrych, A., & Misiura, J. (2024). Analysis of the Accuracy of CAD Modeling in Engineering and Medical Industries Based on Measurement Data Using Reverse Engineering Methods. Designs, 8(3), 50. https://doi.org/10.3390/designs8030050
Turek, P., Bielarski, P., Czapla, A., Futoma, H., Hajder, T., & Misiura, J. (2025). Assessment of Accuracy in Geometry Reconstruction, CAD Modeling, and MEX Additive Manufacturing for Models Characterized by Axisymmetry and Primitive Geometries. Designs, 9(5), 101. https://doi.org/10.3390/designs9050101
Turek, P., Tymczyszyn, J., Habrat, P., & Misiura, J. (2026). Accuracy Assessment of Exhaust Valve Geometry Reconstruction: A Comparative Study of Contact and Optical Metrology in Reverse Engineering. Designs, 10(1), 15. https://doi.org/10.3390/designs10010015
Verykokou, S., & Ioannidis, C. (2023). An Overview on Image-Based and Scanner-Based 3D Modeling Technologies. Sensors, 23(2), 596. https://doi.org/10.3390/s23020596
Vodilka, A., Ko?iško, M., Pollák, M., Kaš?ak, J., & Török, J. (2025). Design of 3D Scanning Technology Using a Method with No External Reference Elements and Without Repositioning of the Device Relative to the Object. Applied Sciences, 15(8), 4533. https://doi.org/10.3390/app15084533
Wakjira, Y., Kurukkal, N. S., & Lemu, H. G. (2024). Assessment of the accuracy of 3D printed medical models through reverse engineering. Heliyon, 10(11), e31829. https://doi.org/10.1016/j.heliyon.2024.e31829
Wang, R., Law, A. C., Garcia, D., Yang, S., & Kong, Z. (2021). Development of structured light 3D-scanner with high spatial resolution and its applications for additive manufacturing quality assurance. The International Journal of Advanced Manufacturing Technology, 117(3–4), 845–862. https://doi.org/10.1007/s00170-021-07780-2
Zhang, X., Luo, L., Ma, R., Wang, Y., Xie, S., Zhang, H., Zou, Y., Wang, X., & Li, X. (2025). Binocular Stereo Vision-Based Structured Light Scanning System Calibration and Workpiece Surface Measurement Accuracy Analysis. Sensors, 25(20), 6455. https://doi.org/10.3390/s25206455
Zhang, Z., Wang, H., Li, Y., Li, Z., Gui, W., Wang, X., Zhang, C., Liang, X., & Li, X. (2025). Fringe-Based Structured-Light 3D Reconstruction: Principles, Projection Technologies, and Deep Learning Integration. Sensors, 25(20), 6296. https://doi.org/10.3390/s25206296
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Copyright (c) 2026 Afferli Seftian, Delima Yanti Sari, Rifelino Rifelino, Zainal Abadi

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