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首页> 外文期刊>Measurement >Minimization of cutting force, temperature and surface roughness through GRA, TOPSIS and Taguchi techniques in end milling of Mg hybrid MMC
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Minimization of cutting force, temperature and surface roughness through GRA, TOPSIS and Taguchi techniques in end milling of Mg hybrid MMC

机译:通过GRA,TOPSIS和TAGUCHI技术最小化切割力,温度和表面粗糙度,在MG Hybrid MMC的最终研磨中

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摘要

Present study investigates the effect of material and machining parameters on cutting force, surface roughness and temperature in end milling of Magnesium (Mg) Metal Matrix Composite (MMC) using carbide tool. Mg hybrid composite was fabricated by reinforcing Cathode Ray Tube (CRT) panel glass, an intensifying E-waste and Boron Nitride (BN) particles through powder metallurgy method. The milling experiments were conducted based on L27 orthogonal array designed by considering CRT glass particle size and weight percentage, tool diameter, speed, feed and depth of cut as input process parameters. Multi objective optimization was done through Grey Relational Analysis (GRA) and Techniques for Order Preferences by Similarity to Ideal Solution (TOPSIS). Both of the techniques provided a similar optimum parameter condition i.e. 10 mu m particle size, 5% reinforcement, 8mm diameter tool, 710 rpm speed, 20 mm/min feed and 0.5mm depth of cut that outcomes in 139.48 N in-feed force, 63.92 N cross-feed force, 42.6 N thrust force, 68.96 degrees C temperature and 0.198 mu m surface roughness. ANOVA is performed to identify significance and also the effect of each process variables on response parameters. Though all the parameters were found to be significant, reinforcement weight% and particle size affects the response parameters as that of machining parameters whereas speed turned to be the least significant factor.
机译:本研究研究了使用碳化物工具对镁(Mg)金属基质复合物(MMC)结束铣削的切割力,表面粗糙度和温度的影响。通过加强阴极射线管(CRT)面板玻璃,通过粉末冶金方法加强阴极射线管(CRT)面板玻璃。通过考虑CRT玻璃粒度和重量百分比,刀具直径,速度,进料和切割的切割作为输入处理参数,进行研磨实验。通过灰色关系分析(GRA)和通过相似性与理想解决方案(TOPSIS)的顺序偏好进行多目标优化。两种技术提供了类似的最佳参数条件,即10μm粒度,5%增强,8mm直径工具,710rpm速度,20mm / min进料和0.5mm切割深度在139.48 n馈电力中的结果, 63.92 n交叉饲料力,42.6升推力,68.96℃温度和0.198μm的表面粗糙度。执行ANOVA以识别显着性,并且还识别每个过程变量对响应参数的影响。虽然发现所有参数都是显着的,但增强重量%和粒度会影响响应参数,因为速度变成了最小因素。

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