Optimizing the uncertainty of measurements on a coordinate measuring machine when controlling complex geometric surfaces

Authors

DOI:

https://doi.org/10.15587/1729-4061.2024.310051

Keywords:

coordinate measuring machine, uncertainty optimization, complex geometric surfaces, adaptive measurement strategy, measurement uncertainty, Monte Carlo method, quality control, industrial metrology, measurement automation, high-precision manufacturing

Abstract

The object of this study is the process of optimizing measurement uncertainty on a coordinate measuring machine (CMM) when inspecting complex geometric surfaces. The problem addressed was insufficient accuracy and efficiency of measurements of complex parts on CMMs under production conditions. A method for optimizing measurement uncertainty has been devised, which includes a mathematical model of the measurement process and an adaptive algorithm for optimizing the control strategy, based on the Monte Carlo method. The model takes into account the geometry of surfaces and CMM characteristics, while the algorithm dynamically adjusts measurement parameters. The results demonstrate a reduction in measurement uncertainty by 15–20 % and a reduction in inspection time by 10–12 % compared to conventional methods. This is achieved by taking into account the specificity of complex surface geometry and an adaptive approach.

The uniqueness of the developed method is the ability to automatically adapt to different types of CMMs and measured objects, optimizing the number and location of measurement points, the speed of probe movement, and its contact force with the surface. The method takes into account not only the geometric parameters of objects but also the characteristics of the CMM itself, which allows for high accuracy. The method is particularly effective for parts with complex geometry, in which conventional methods often lead to significant errors.

Practical application is possible at machine-building enterprises for quality control of complex parts, especially in serial production. The implementation of the developed method allows for improving product quality and reducing production costs by 8–10 % due to optimization of the control process and reduction of defects

Author Biographies

Volodymyr Kvasnikov, National Aviation University

Doctor of Technical Sciences, Professor, Honored Metrologist of Ukraine

Department of Computerized Electrical Systems and Technologies

Oleg Chalyi, National Aviation University

PhD Student

Department of Computerized Electrical Systems and Technologies

Maryna Graf, Zhytomyr Polytechnic State University

Doctor of Philosophy (PhD), Head of Department

Department of Computer Science

Anatolii Perederko, State University of Intellectual Technologies and Communications

Doctor of Technical Sciences, Associate Professor

Department of Metrology, Quality and Standardization

References

  1. Liao, Z.-Y., Wang, Q.-H., Xu, Z.-H., Wu, H.-M., Li, B., Zhou, X.-F. (2024). Uncertainty-aware error modeling and hierarchical redundancy optimization for robotic surface machining. Robotics and Computer-Integrated Manufacturing, 87, 102713. https://doi.org/10.1016/j.rcim.2023.102713
  2. Ziętarski, S., Kachel, S., Benaouali, A. (2016). Coordinate measuring machine uncertainty analysis using the combinatorial cyclic method of optimization. Mechanik, 7, 876–877. https://doi.org/10.17814/mechanik.2016.7.216
  3. Zhao, X., Ji, L., Zhao, L. (2018). Calibration of Parallelism Error About Rotating Shafts Based on the Three-coordinate Measuring Machine. Proceedings of the 2nd International Conference on Intelligent Manufacturing and Materials. https://doi.org/10.5220/0007532203790383
  4. Shen, M., Yang, H., Chang, D., Jiang, X., Hu, Y. (2024). Dynamic error modeling and analysis of articulated arm coordinate measuring machine with integrated joint module. Measurement Science and Technology, 35 (6), 065022. https://doi.org/10.1088/1361-6501/ad35de
  5. Cheung, C., Ren, M., Kong, L., Whitehouse, D. (2014). Modelling and analysis of uncertainty in the form characterization of ultra-precision freeform surfaces on coordinate measuring machines. CIRP Annals, 63 (1), 481–484. https://doi.org/10.1016/j.cirp.2014.03.032
  6. Zhuang, Q., Wan, N., Guo, Y., Zhu, G., Qian, D. (2024). A state-of-the-art review on the research and application of on-machine measurement with a touch-trigger probe. Measurement, 224, 113923. https://doi.org/10.1016/j.measurement.2023.113923
  7. Wojtyła, M., Rosner, P., Płowucha, W., Forbes, A. B., Savio, E., Balsamo, A. (2022). Validation of the sensitivity analysis method of coordinate measurement uncertainty evaluation. Measurement, 199, 111454. https://doi.org/10.1016/j.measurement.2022.111454
  8. Zhang, M., Liu, D., Liu, Y. (2024). Recent progress in precision measurement and assembly optimization methods of the aero-engine multistage rotor: A comprehensive review. Measurement, 235, 114990. https://doi.org/10.1016/j.measurement.2024.114990
  9. Wozniak, A., Krajewski, G., Byszewski, M. (2019). A new method for examining the dynamic performance of coordinate measuring machines. Measurement, 134, 814–819. https://doi.org/10.1016/j.measurement.2018.12.041
  10. Hu, Y., Zhao, R., Ju, B. (2021). Geometric analysis of measurement errors in a surface metrology class with closed-loop probes. Measurement, 184, 109869. https://doi.org/10.1016/j.measurement.2021.109869
  11. Yan, Y., He, G., Sang, Y., Yao, C., Wang, S., Chen, F. (2022). A two-module automated scanning inspection planning methodology for complex surfaces on coordinate measuring machine. Measurement, 202, 111827. https://doi.org/10.1016/j.measurement.2022.111827
  12. Xing, T., Zhao, X., Song, L., Cui, Z., Zou, X., Sun, T. (2022). On-machine measurement method and geometrical error analysis in a multi-step processing system of an ultra-precision complex spherical surface. Journal of Manufacturing Processes, 80, 161–177. https://doi.org/10.1016/j.jmapro.2022.05.057
  13. Sato, O., Takatsuji, T., Matsuzaki, K., Watanabe, M., Kajima, M., Miura, Y., Nakanishi, S. (2024). Practical experimental design and uncertainty evaluation method for dimensional and form measurements using coordinate measuring machines. Measurement, 227, 114224. https://doi.org/10.1016/j.measurement.2024.114224
  14. Ren, M., Cheung, C., Kong, L., Wang, S. (2015). Quantitative Analysis of the Measurement Uncertainty in Form Characterization of Freeform Surfaces Based on Monte Carlo Simulation. Procedia CIRP, 27, 276–280. https://doi.org/10.1016/j.procir.2015.04.078
  15. Wang, Z., He, X., Wang, Y. (2021). Different measuring methods of REVO five-axis coordinate measuring machine. Tenth International Symposium on Precision Mechanical Measurements. https://doi.org/10.1117/12.2613428
  16. Internet-Based Surface Metrology Algorithm Testing System. National Institute of Standards and Technology. Available at: https://physics.nist.gov/VSC/jsp/About.jsp
  17. D Metrology Use Cases. GOM GmbH.
  18. Example Studies. Digital Surf. Available at: https://www.digitalsurf.com/
  19. An opensource on-machine 3D Scanner CMM (Coordinate Measuring Machine) system. OpenCMM. Available at: https://github.com/OpenCMM/OpenCMM
  20. Sousa, A. R. (2018). Metrological evaluation of a Coordinate Measuring Machine with 5-axis measurement technology. Procedia CIRP, 75, 367–372. https://doi.org/10.1016/j.procir.2018.04.035
  21. Nasir, S. S. M., Hussin, N., Fohimi, N. A. M., Ibrahim, D., Wahab, R. M. (2023). Design Improvement and Fabrication of a Jig for Holding a Workpiece in a Coordinate Measuring Machine. Progress in Engineering Technology V, 197–206. https://doi.org/10.1007/978-3-031-29348-1_21
Optimizing the uncertainty of measurements on a coordinate measuring machine when controlling complex geometric surfaces

Downloads

Published

2024-08-28

How to Cite

Kvasnikov, V., Chalyi, O., Graf, M., & Perederko, A. (2024). Optimizing the uncertainty of measurements on a coordinate measuring machine when controlling complex geometric surfaces . Eastern-European Journal of Enterprise Technologies, 4(5 (130), 14–25. https://doi.org/10.15587/1729-4061.2024.310051

Issue

Section

Applied physics