Surface roughness study of polyamide in nano-metric polishing using low-frequency acoustic energy

机械加工 材料科学 表面粗糙度 抛光 磨料 表面光洁度 机械工程 有限元法 复合材料 结构工程 工程类 冶金
作者
Sajjad Beigmoradi,Mehrdad Vahdati
出处
期刊:Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture [SAGE Publishing]
卷期号:236 (6-7): 981-996 被引量:4
标识
DOI:10.1177/09544054211057375
摘要

Polymers have gained the attention of manufacturers due to their significant advantages such as low density, high corrosion resistance, and high humidity resistance. Producing high-precision polymeric components is one the most challenging issues especially in fabricating complex or micro-scale systems. Some of the machining techniques such as electro discharge machining (EDM) and electrochemical machining (ECM) cannot be employed for machining the non-conductive parts. Using abrasive particles is one of the best options for machining these types of materials. In this work, the capability of the acoustic energy for machining polyamide (PA) workpieces is studied. To this end, an experimental setup is installed and design of experiment (DoE) algorithm is employed to survey the effect of process parameters on surface roughness. Three parameters at three levels are considered as the effective factors of the process and the sensitivity of the surface roughness on the process factors is investigated. In the next step, a hybrid finite element/boundary element approach was used to discuss the relation of process parameters to the vibrational characteristics of the container, then the mechanism of the process was investigated employing the discrete element method. Finally, the surface topology of the optimal workpiece before and after the process was presented and compared. It was observed that acoustic energy can be considered as a vibration source of the container’s floor to provide kinetic energy for machining PA parts on the nano-metric scale. Moreover, it was found that the initial roughness of the workpiece and the chosen parameters play a crucial role in the machining process. Experimental results show that in this technique by selecting appropriate process factors the surface roughness can be reduced up to 50%.

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