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Influence cutting parameters on the surface quality and corrosion behavior of Ti-6Al-4V alloy in synthetic body environment (SBF) using Response Surface Method

机译:响应面法研究切削参数对合成体环境中Ti-6Al-4V合金表面质量和腐蚀行为的影响

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摘要

Most of the global manufacturing of titanium alloys is related to produce biphasic structures with grains alpha and beta. The development of modern applications of titanium alloy is a great challenge due to the chemical composition of Ti-6Al-4V alloy and the complexity of the manufacturing technology. This study proposed an optimal investigation of the variation of cutting speed, feed rate, and depth of cut in the turning of Ti-6Al-4V alloy on surface roughness, cutting efforts, and corrosion resistance. Response Surface Method has been established to optimize and model the responses mathematically. The adequacy of the models and a significant contribution of parameters were determined by analysis of variance (ANOVA). The biocompatibility of the machined surface for different cutting parameters was evaluated by the electrochemical polarization in simulated body fluids (SBF). Furthermore, desirability function analysis was used to determine the optimal values for surface quality, the turning force, and the passivation rate. It was clearly noticed that the multi-responses of the desirability function improved the machine process. The feed rate and depth of cut were the most relevant factors to minimize surface roughness and the turning forces. Moreover, the experimental results showed that the corrosion behavior was strongly related to minimal surface roughness. Finally, the optimization reduced the surface roughness Ra and Rz in 5.5% and 11.9%, respectively and increased the corrosion resistance in 18.8%. (C) 2016 Elsevier Ltd. All rights reserved.
机译:钛合金的全球制造中的大多数与产生具有α和β晶粒的双相结构有关。由于Ti-6Al-4V合金的化学成分和制造技术的复杂性,钛合金现代应用的发展是一个巨大的挑战。这项研究提出了关于Ti-6Al-4V合金车削时切削速度,进给速度和切削深度变化对表面粗糙度,切削强度和耐腐蚀性的最佳研究。已经建立了响应面方法,以数学方式优化和建模响应。通过方差分析(ANOVA)确定模型的充分性和参数的显着贡献。通过模拟体液(SBF)中的电化学极化,评估了加工表面对于不同切割参数的生物相容性。此外,使用期望函数分析来确定表面质量,转向力和钝化率的最佳值。清楚地注意到,期望功能的多重响应改善了机器过程。进给速度和切削深度是最小化表面粗糙度和车削力的最重要因素。此外,实验结果表明,腐蚀行为与最小的表面粗糙度密切相关。最后,优化使表面粗糙度Ra和Rz分别降低了5.5%和11.9%,而耐腐蚀性提高了18.8%。 (C)2016 Elsevier Ltd.保留所有权利。

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