New fast micro-topography estimation algortihms for 5 axis milling
• Development of Three Improved Algorithms : We have proposed three new algorithms based on the classical Z-map method, aiming to enhance both the accuracy and computational efficiency in predicting micro-topography in 5-axis milling. • Enhanced Computational Efficiency : By introducing a parallelized version of the Z-map (MOD1) and a rounding technique (MOD3), we have achieved a significant reduction in computation time. This improvement may help in making real-time applications more feasible. • Validation through Experiments : We conducted extensive experimental tests under various machining conditions to validate our algorithms. The results suggest that our methods can effectively enhance the prediction of machined surfaces in practical settings. Accurately predicting the topography of machined surfaces is vital in industries like aerospace, automotive, and biomedical manufacturing. This paper introduces a novel methodology for fast and precise areal surface micro-topography prediction in 5-axis CNC milling, particularly for finishing processes using ball-end milling tools. Although commercial CAM software can predict the macro-topography of a machined surface, incorporating the cutter edge geometry and its rotational movement is essential for accurately predicting the surface's micro-topography. In this work, three alternative algorithms based on the Z-Map method are proposed: (1) a parallelized version of Z-Map (MOD1) for increased computational efficiency, (2) a swept surface technique (MOD2) for more accurate simulations, and (3) a rounding technique (MOD3) for rapid, precise topography prediction by aligning cutter edge points. The user can choose one of the three algorithms based on computational resources and preferences. These are validated through experimental tests on a 5-axis milling machine under different machining conditions. The results demonstrate that the developed algorithms enhance the prediction of the machined surface's micro-topography, significantly reducing computation time and improving accuracy compared to the traditional Z-map method.
Authors
- José Antonio Albajez (ORCID: https://orcid.org/0000-0003-4839-0610)
- Sergio Aguado (ORCID: https://orcid.org/0000-0001-8689-6482)
- Yasser Zekalmi (ORCID: https://orcid.org/0009-0004-1650-3670)
- María José Oliveros
Institutions
- Universidad de Zaragoza (ES)
Publication Details
- Journal
- Advances in Engineering Software
- Published
- 2025-03-07
- DOI
- https://doi.org/10.1016/j.advengsoft.2025.103909
- Citations
- 1
- Primary Topic
- Advanced machining processes and optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.71
Funders
- European Commission
- Universidad de Zaragoza