Optimization of machining parameters during end milling of super alloys using Grey based Taguchi method coupled with entropy measurement technique

R. Sreenivasulu, C. S. Rao
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引用次数: 2

Abstract

: High-quality products include those with better surface quality and texture, close dimensional tolerances and form accuracies at precise level, increase fatigue life and burr-free. Burr formation is one of the most common inevitable facts occurring in all material removal processes, reduces assembly and machined part quality. But, burr formation during milling is a more complex mechanism compare to remaining machining burrs and leads to numerous difficulties during the deburring process. To prevent this, one should optimize the combination of cutting parameters during machining itself. In order to build up a link between quality and productivity and to attain the same in the cost-effective way, the present work concentrate on multi objective optimization of CNC end milling process parameters. Multiple performance characteristics with respect to surface quality and performance index like assembly work have been put up, to assess an equivalent single quality index (called grey relational grade) has been optimized finally by Grey based Taguchi method. After that priority weight of individual quality and performance attributes has been estimated by entropy measurement technique on the basis of relative significance and check the feasibility of the proposed technique has been demonstrated in this context.
基于灰色的田口法结合熵测量技术优化高温合金立铣削加工参数
:高质量的产品包括表面质量和质地更好,尺寸公差接近,形状精度达到精密水平,增加疲劳寿命和无毛刺。毛刺的形成是所有材料去除过程中最常见的不可避免的事实之一,它降低了装配和加工零件的质量。但是,铣削过程中毛刺的形成是一个比剩余的加工毛刺更复杂的机制,并导致在去毛刺过程中的许多困难。为了防止这种情况,应在加工过程中优化切削参数的组合。为了建立质量与生产率之间的联系,并以经济高效的方式实现质量与生产率之间的联系,对数控立铣削工艺参数进行了多目标优化。提出了与表面质量和装配作业等性能指标相关的多个性能特征,最后采用基于灰色的田口法对一个等效的单一质量指标(称为灰色关联度)进行了优化。然后,在相对显著性的基础上,利用熵值测量技术估计了个体质量和性能属性的优先权重,并验证了该方法的可行性。
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