Manufacturing Technology 2025, 25(1):95-102 | DOI: 10.21062/mft.2025.014

Optimization of Zero-Point Setting for Enhanced Measurement Accuracy

Miroslav Matuš ORCID...1, Mário Drbúl ORCID...1, Jaromír Markovič ORCID...1, Michal Šajgalík ORCID...1, Andrej Czán ORCID...1, Miroslav Cedzo ORCID...1, Richard Joch ORCID...1, Martin Novák ORCID...2, Jana Petru ORCID...3
Faculty of Mechanical Engineering, University of Zilina, Univerzitna 8215/1, 010 26 Zilina, Slovakia
Faculty of Mechanical Engineering, J. E. Purkyne University in Usti nad Labem, Pasteurova 3334/7, 400 01 Usti nad Labem. Czech Republic
Faculty of Mechanical Engineering, VSB – Technical University of Ostrava, 17. listopadu 2172/15, 708 00 Ostrava, Czech Republic

The precise setting of the zero point represents a critical factor in non-contact measurement of mechani-cal components, particularly in areas such as the engineering and automotive industries, where high accuracy is key to quality control. This study analyzes the impact of various alignment methods—specifically the best-fit method and the datum method (3–2–1)—on the measurement results of complex geometric shapes. Experimental measurements were conducted using a laser scanner and Polyworks 2015 software. The results indicate that the best-fit method achieves higher accuracy when measuring complex and freely oriented shapes, while the 3–2–1 method provides more consistent results for simply defined geometries. These findings confirm the importance of proper alignment method selection in op-timizing non-contact measurement processes and offer new insights for improving efficiency in industrial quality control.

Keywords: Metrology, Best fit, Non-contact Measurement, Coordinate System
Grants and funding:

This research was funded by the University of Žilina project APVV-22-0328: “ Design of a Methodology and its Verification for the Measurement of Selected Parameters of Ti Implants in the Manufacturing Process”, APVV-23-0366: “ Research on the Reference Benchmark and Measurement Methods Ensuring the Determination of the Relationship between Geometric Specifications and Qualitative Indicators of 3D Objects Manufactured by Additive Technologies”, Kega project 028ŽU-4/2022: “ Implementation of innovative approaches to student education in the field of 3D metrology”, KEGA 025STU-4/2024: “ Development of soft skills of university students in technically oriented subjects”, and KEGA 017/ZU-4/2022: "Implementation of digital technologies and simulations into the teaching process of machining technology"

Received: December 8, 2024; Revised: March 12, 2025; Accepted: March 12, 2025; Prepublished online: March 27, 2025; Published: April 25, 2025  Show citation

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Matuš M, Drbúl M, Markovič J, Šajgalík M, Czán A, Cedzo M, et al.. Optimization of Zero-Point Setting for Enhanced Measurement Accuracy. Manufacturing Technology. 2025;25(1):95-102. doi: 10.21062/mft.2025.014.
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References

  1. SALEH, H. R., AHMAD REZA. (2024). An improved iterative closest point algorithm based on the particle filter and K-means clustering for fine model matching. The Visual Computer, pp. 7589-7607. DOI: https://doi.org/10.1007/s00371-023-03195-0. Go to original source...
  2. ZHANG, X., WANG, J., & WANG, Y. (2024). Precision Optical Metrology and Smart Sensing. Sensors, 24(21), pp. 6816. DOI: https://doi.org/10.3390/s24216816. Go to original source...
  3. SAMELOVÁ, V., MAREK, T., JELÍNEK, A., JANKOVYCH, R., MARADOVÁ, K., & HOLUB, M. (2024). A Case Study on Assessing the Capability and Applicability of an Articulated Arm Coordinate Measuring Machine and a Touch-Trigger Probe for On-Machine Measurement. Machines, 12(12), 841. https://doi.org/10.3390/machines12120841 Go to original source...
  4. ADELEKE, A. K., ANI, E. C., OLU-LAWAL, K. A., OLAJIGA, O. K., PORTILLO MONTERO, D. J. (2024). Future of precision manufacturing: Integrating advanced metrology and intelligent monitoring for process optimization. International Journal of Science and Research Archive, 11(01), pp. 2346-2355. DOI: https://doi.org/10.30574/ijsra.2024.11.1.0335. Go to original source...
  5. WANG, Z., HU, J., SHI, Y., CAI, J., PI, L. (2024). Target Fitting Method for Spherical Point Clouds Based on Projection Filtering and K-Means Clustered Voxelization. Sensors, 24(17), pp. 5762. DOI: https://doi.org/10.3390/s24175762. Go to original source...
  6. ZHANG, Y., LIU, J., & LAI, T. (2024). Smart Manufacturing and Digitalization of Metrology. Journal of Advanced Metrology, 18(3), pp. 251-267. DOI: https://doi.org/10.1016/j.jam.2024.03.005 Go to original source...
  7. WANG, H., ZHOU, X., & CHEN, B. (2024). Digital Avatar of Metrology: Enhancing Measurement Accuracy and Automation. International Journal of Precision Engineering, 29(7), pp. 1125-1140. DOI: https://doi.org/10.1016/j.ijpe.2024.07.010 Go to original source...
  8. BENATTIA, B., B. A. (2024). Automation of three-dimensional inspection using the iterative closest point algorithm: application to a gas turbine blade. The International Journal of Advanced Manufacturing Technology, pp. 4703-4713. DOI: https://doi.org/10.1007/s00170-024-13866-4. Go to original source...
  9. CHRISTOPH, M. (2008). Alignment and stability in industrial measurement using 3-2-1 technique. Metrol-ogy Journal, pp. 411-417.
  10. KIRACI, E., G. A. (2016). Evaluating the capability of laser scanning to measure an automotive artefact: a comparison study of touch trigger probe and laser-scanning. International Journal of Productivity and Quality Management (IJPQM). DOI: https://doi.org/10.1504/IJPQM.2016.077776 Go to original source...
  11. WANG, Z., HU, J., SHI, Y., CAI, J., PI, L. (2024). Target Fitting Method for Spherical Point Clouds Based on Projection Filtering and K-Means Clustered Voxelization. Sensors, 24(17), pp. 5762. DOI: https://doi.org/10.3390/s24175762. Go to original source...
  12. EL-MELEGY, M. T. (2007). Non-iterative approach to best fit matching for exact calibration in coordinate metrology. Computer-Aided Design, pp. 789-796.
  13. FAN, K. C. (2000). Measurement accuracy enhancement in three-dimensional coordinate metrology using best-fit algorithms. pp. 128-137.
  14. LI, S., KANG, H., LI, Z., ZHOU, Y., ZHANG, Y., LIU, J., & LAI, T. (2024). Development of a Large-Aperture Coordinate Precision Measurement Instrument Using Differential Geometric Error Weighting. Applied Sciences, 14(22), pp. 10125. DOI: https://doi.org/10.3390/app142210125. Go to original source...
  15. RIKARDO, M., A. A. (2014). Framework for verification of positional tolerances with a 3D non-contact measurement method. International Journal on Interactive Design and Manufacturing (IJIDeM), pp. 85-93. DOI: https://doi.org/10.1007/s12008-014-0214-7. Go to original source...
  16. MINETOLA, P. (2012). The Importance of a Correct Alignment in Contactless. International Journal of Precision Engineering and Manufacturing, pp. 211-218. DOI: https://doi.org/10.1007/s12541-012-0026-2 Go to original source...
  17. PEARN, B. S. (1993). Alignment metrology. Optical Methods in Engineering Metrology, pp. 87-112. DOI: https://doi.org/10.1007/978-94-011-1564-3_3. Go to original source...
  18. RAINER, M., M. V.-S. (2019). Best-fit method for the calibration of 3D objects using a laser line sensor mounted on the flange of an articulated robot. Tagungsband des 4. Kongresses Montage Handhabung Industrier-oboter, pp. 207-216. DOI: https://doi.org/10.1007/978-3-662-59317-2_21. Go to original source...
  19. WARSZA, Z. L., PUCHALSKI, J., WIĘCEK, T. (2024). Novel Method of Fitting a Nonlinear Function to Data of Measurement Based on Linearization by Change Variables, Examples and Uncertainty. Metrology, 4(4), pp. 718-735. DOI: https://doi.org/10.3390/metrology4040042. Go to original source...
  20. ANASIEWICZ, K., JÓZWIK, J., LELEŃ, M., PIEŚKO, P., LEGUTKO, S., TOMCZAK, J., PATER, Z., BULZAK, T. (2024). Identification of Internal Defects in Forged Shafts by Measurement of Residual Stresses Using X-Ray Method. Manufacturing Technology, 24(5), pp. 711-720. DOI: 10.21062/mft.2024.086. Go to original source...
  21. SAŁAMACHA, D., JÓZWIK, J. (2023). Evaluation of Measurement Uncertainty Obtained with a Tool Probe on a CNC Machine Tool. Manufacturing Technology, 23(4), pp. 513-524. DOI: 10.21062/mft.2023.051. Go to original source...

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