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医用级镍钛诺记忆合金电火花线切割加工的可加工性分析与优化

Machinability Analysis and Optimization in Wire EDM of Medical Grade NiTiNOL Memory Alloy.

作者信息

Kulkarni Vinayak N, Gaitonde V N, Karnik S R, Manjaiah M, Davim J Paulo

机构信息

School of Mechanical Engineering, KLE Technological University, Hubballi, Karnataka 580 031, India.

Department of Electrical and Electronics Engineering, KLE Technological University, Hubballi, Karnataka 580 031, India.

出版信息

Materials (Basel). 2020 May 9;13(9):2184. doi: 10.3390/ma13092184.

Abstract

NiTiNOL (Nickel-Titanium) shape memory alloys (SMAs) are ideal replacements for titanium alloys used in bio-medical applications because of their superior properties like shape memory and super elasticity. The machining of NiTiNOL alloy is challenging, as it is a difficult to cut material. Hence, in the current research the experimental studies on machinability aspects of medical grade NiTiNOL SMA during wire electric discharge machining (WEDM) using zinc coated brass wire as electrode material have been carried out. Pulse time (T), pause time (T), wire feed (WF), and servo voltage (SV) are chosen as varying input process variables and the effects of their combinational values on output responses such as surface roughness (SR), material removal rate (MRR), and tool wear rate (TWR) are studied through response surface methodology (RSM) based developed models. Modified differential evolution (MDE) optimization technique has been developed and the convergence curve of the same has been compared with the results of differential evolution (DE) technique. Scanning electron microscopy (SEM) and energy dispersive X-ray spectrography (EDS) analysis are carried out to study the surface morphology of the machined alloy. SV is found to be more influential process parameter for achieving better MRR with minimal SR and TWR, followed by T, T, and WF. The WF has good impact on reduced SR and TWR responses and found to be least significant in maximizing MRR.

摘要

镍钛诺(镍 - 钛)形状记忆合金(SMA)因其形状记忆和超弹性等优异性能,是生物医学应用中钛合金的理想替代品。镍钛诺合金的加工具有挑战性,因为它是一种难切削材料。因此,在当前的研究中,使用镀锌黄铜丝作为电极材料,对医用级镍钛诺形状记忆合金在电火花线切割加工(WEDM)过程中的可加工性进行了实验研究。选择脉冲时间(T)、停歇时间(t)、丝速(WF)和伺服电压(SV)作为变化的输入工艺参数,并通过基于响应面方法(RSM)开发的模型研究它们的组合值对诸如表面粗糙度(SR)、材料去除率(MRR)和工具磨损率(TWR)等输出响应的影响。开发了改进的差分进化(MDE)优化技术,并将其收敛曲线与差分进化(DE)技术的结果进行了比较。进行了扫描电子显微镜(SEM)和能量色散X射线光谱仪(EDS)分析,以研究加工后合金的表面形貌。发现SV是实现更好的MRR、最小化SR和TWR的更具影响力的工艺参数,其次是T、t和WF。WF对降低SR和TWR响应有良好影响,并且发现在最大化MRR方面最不显著。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb4b/7254380/50f5ce44ab1f/materials-13-02184-g001.jpg

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