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首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part B. Journal of engineering manufacture >Surface roughness optimization in processing SiC monocrystal wafers by wire saw machining with ultrasonic vibration
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Surface roughness optimization in processing SiC monocrystal wafers by wire saw machining with ultrasonic vibration

机译:超声振动线锯加工SiC单晶晶片的表面粗糙度优化

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摘要

Being very hard and highly brittle, silicon carbide (SiC) monocrystal is considered to be a difficult-to-machine material. The machining method and process parameters greatly affect the productivity and the surface quality of the finished part. This article presents an experimental investigation of processing SiC monocrystal wafers by wire saw machining with ultrasonic vibration. Experiments are conducted for various process parameters, which include wire saw velocity, part feed rate, part speed and ultrasonic vibration amplitude. An empirical model has been developed for predicting the surface roughness when wire saw machining SiC monocrystal wafers. Response surface regression and analysis of variance are used to study the effects of the process parameters. Optimum process parameters for minimizing surface roughness are determined using the desirability functional approach. The experimental results showed that the surface roughness model can predict the surface roughness with a relative error lower than 5% when wire saw machining SiC monocrystal wafers over a range of process parameters.
机译:碳化硅(SiC)单晶非常坚硬且高度脆,被认为是难于加工的材料。加工方法和工艺参数极大地影响了成品的生产率和表面质量。本文介绍了通过超声振动线锯加工来处理SiC单晶晶片的实验研究。针对各种工艺参数进行了实验,包括线锯速度,零件进给速度,零件速度和超声振动幅度。已经开发了用于预测线锯加工SiC单晶晶片时表面粗糙度的经验模型。使用响应面回归和方差分析来研究过程参数的影响。使用合意性功能方法确定使表面粗糙度最小的最佳工艺参数。实验结果表明,当在一系列工艺参数上用线锯机加工SiC单晶晶片时,表面粗糙度模型可以预测表面粗糙度,且相对误差低于5%。

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