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Optimization Studies on Thrust Force and Torque during Drilling of Natural Fiber Reinforced Sandwich Composites

机译:天然纤维增强夹芯复合材料钻削过程中推力和扭矩的优化研究

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This research is carried out to investigate thrust force and torque during drilling on the developed bio-degradable sandwich composites. Two natural fibers, namely vetiveria zizaniodes (vetiver) and jute, and one synthetic fiber, namely Eglass, are used as reinforcements with vinyl ester resin to form three composite specimens. The fiber compositions in each specimen are varied while the resin composition is kept as a constant. The vetiver fibers are pre-treated with alkali and followed by furnace heating in order to improve its surface properties. The specimens are subjected to a set of 28 drilling operations during which the machining parameters, like speed, feed rate, tool point angle and work sample, are varied between four levels to form a four-factor mixed level D-optimal factorial design. During each drilling operation, the thrust force and torque are measured as responses by using a kistler make drill dynamometer with an accuracy level of 0.01N. The responses are analyzed by using response surface method, and non-linear regression equations are developed. Optimization on the experimental data resulted in selection of a high level of speed of 2000 rpm, low level feed of 0.1 mm/rev, tool angle between 600 to 900 and selection of sample level I as optimized values with a thrust force of 82.47 N and torque of 4.4 Nm. Confirmatory runs are conducted and the responses are again measured. The average error between the developed model and the confirmatory runs is found to be minimal and hence the optimization is highly satisfactory.
机译:进行这项研究以研究开发的可生物降解夹芯复合材料在钻进过程中的推力和扭矩。两种天然纤维,即香根草和黄麻,以及一种合成纤维,即Eglass,被乙烯基酯树脂用作增强材料,形成了三个复合样品。在使树脂组成保持恒定的同时,改变每个样品中的纤维组成。香根草纤维用碱预处理,然后通过加热炉加热以改善其表面性能。对样品进行28组钻孔操作,在此过程中,加工参数(例如速度,进给速度,刀尖角度和工作样品)在四个级别之间变化,以形成四因子混合级别D最优因子设计。在每次钻孔操作中,使用精度为0.01N的奇石马力测功机测量推力和扭矩作为响应。使用响应面法分析响应,并建立非线性回归方程。通过对实验数据进行优化,可以选择2000 rpm的高转速,0.1 mm / rev的低进给量,600至900之间的刀具角度以及选择I级样品作为最佳推力为82.47 N和扭矩为4.4 Nm。进行验证性运行,并再次测量响应。发现开发的模型与验证运行之间的平均误差最小,因此优化非常令人满意。

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