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Optical surface generation on additively manufactured AlSiMg0.75 alloys with ultrasonic vibration-assisted machining
Journal of Materials Processing Technology ( IF 6.7 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.jmatprotec.2020.116597
Yuchao Bai , Zhuoqi Shi , Yan Jin Lee , Hao Wang

Abstract Additive manufacturing technology provides a feasible solution to directly manufacture optical components with complex functional structure. However, the poor surface quality and low relative density result in the limitation on its rapid application. In order to overcome the above shortcomings, process optimization and ultrasonic elliptical vibration-assisted machining (UEVAM) were used in the fabrication of optical surfaces on selective laser melted (SLM) AlSiMg0.75 alloy. The optimised energy density in the SLM process was identified ranging from 65 to 130 J/mm3 with the highest achievable relative density of 99.6 %. Post-processing heat treatment changed the cellular/dendritic microstructure of as-built samples to an α-Al matrix embedded with Si particles, which reduced the microcutting forces by 27.67 % and improved the machined surface roughness (Ra) by 8.7 % during conventional microcutting. In contrast, the UEVAM process is capable of further improving the surface quality from 11.03–5.1 nm Ra, without heat treatment. It is also evident that poor machined surface quality was attributed to the formation of oxide particles during SLM. Chip morphology analysis and finite element method simulations revealed the benefits of UEVAM in tackling the issue of precipitation and extended our understanding of the applications of UEVAM.

中文翻译:

使用超声波振动辅助加工在增材制造的 AlSiMg0.75 合金上生成光学表面

摘要 增材制造技术为直接制造功能结构复杂的光学元件提供了可行的解决方案。然而,其表面质量差和相对密度低,限制了其快速应用。为了克服上述缺点,在选择性激光熔化(SLM)AlSiMg0.75合金上采用工艺优化和超声椭圆振动辅助加工(UEVAM)制造光学表面。SLM 工艺中优化的能量密度范围为 65 至 130 J/mm3,最高可实现相对密度为 99.6%。后处理热处理将竣工样品的蜂窝/树枝状微观结构改变为嵌入 Si 颗粒的 α-Al 基体,从而将显微切削力降低了 27。67 % 并在常规微切削过程中将加工表面粗糙度 (Ra) 提高了 8.7 %。相比之下,UEVAM 工艺能够在不进行热处理的情况下进一步提高 11.03-5.1 nm Ra 的表面质量。很明显,较差的加工表面质量归因于 SLM 过程中氧化物颗粒的形成。芯片形态分析和有限元方法模拟揭示了 UEVAM 在解决沉淀问题方面的优势,并扩展了我们对 UEVAM 应用的理解。
更新日期:2020-06-01
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