Affiliation:
1. National University of Singapore
Abstract
Abstract
Polishing abrasives play a crucial role in polishing and significantly influence the polishing rate and quality. Current research on direct observation of abrasives under polishing tools with complicated surface textures is limited. In this work, high speed camera is applied to observe the abrasives under morphable polishing tools with smooth, labyrinth and dimple textures at the tool rotational speed (300, 600 and 900 rpm) and tool offset (0.2, 0.5 and 1 mm). The results shows that the number of abrasives in the contact area is increased with the tool rotational speed and decreased with the tool offset. Among the three tools, dimple tools retain more abrasives than labyrinth and smooth tools. Abrasive trajectories are nearly horizontal, in accordance with the polishing velocity direction. The velocity magnitude is mainly influenced by the horizontal velocity u, as the vertical velocity v is relatively small. The velocity magnitude increases with the tool rotational speed and the tool offset. Among the three tools, the velocity is higher under labyrinth and dimple tools than under smooth tools. The pressure and abrasive velocity were increased by ~ 25% and 70%, while the resultant removal volume was increased by 54.2% with a dimple tool than a labyrinth tool.
Publisher
Research Square Platform LLC
Reference35 articles.
1. 1. Fang, F.Z., et al., Manufacturing and measurement of freeform optics. CIRP Annals, 2013. 62(2): p. 823–846.
2. 2. Martin, H., et al. Fabrication and testing of the first 8.4-m off-axis segment for the Giant Magellan Telescope. in Modern Technologies in Space-and Ground-based Telescopes and Instrumentation. 2010. SPIE.
3. 3. Axinte, D.A., et al., Investigations on belt polishing of heat-resistant titanium alloys. Journal of Materials Processing Technology, 2005. 166(3): p. 398–404.
4. 4. Zhang, S.J., et al., A review of surface roughness generation in ultra-precision machining. International Journal of Machine Tools and Manufacture, 2015. 91: p. 76–95.
5. 5. Kadirgama, K., et al., Surface roughness prediction model of 6061-T6 aluminium alloy machining using statistical method. European Journal of Scientific Research, 2009. 25(2): p. 250–256.