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MULTIOBJECTIVE OPTIMIZATION OF END MILLING HCHCr USING AlCrN PVD COATED CUTTERS WITH MOGA AND RSMO

机译:使用带有Moga和RSMO的AlCrN PVD涂层切削刀对HCHCr端铣削的多目标优化

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Here the End milling is studied for optimization of responses such as surface roughness and tool wear while machining HCHCr. These two conflicting responses decide the quality of process; therefore the multiobjective optimization technique is used. The Response Surface Optimizer (RSMO) and Multiobjective Genetic Algorithm (MOGA) were used as the multiobjective optimization techniques. The PVD coating of 2.5 micron AlCrN was used on four flute HSS End milling cutter. Input machining parameters were cutting speed, feed rate, depth of cut and percentage concentration of the solid lubricant MoS_2 mixed with SAE-20 base oil. The experimentation was carried out using two level full factorial design concept while ANOVA technique has been used to verify the adequacy of mathematical model. It was found that the cutting speed (V) is having most dominant role on surface roughness and tool wear. The sensitivity analysis was carried out for studying sensitivity of input parameters for the responses.
机译:在这里,对立铣刀进行了研究,以优化加工HCHCr时的响应,例如表面粗糙度和刀具磨损。这两个相互矛盾的响应决定了过程的质量。因此,使用了多目标优化技术。响应面优化器(RSMO)和多目标遗传算法(MOGA)被用作多目标优化技术。 2.5微米AlCrN的PVD涂层在四刃HSS立铣刀上使用。输入的加工参数为切削速度,进给速度,切削深度和与SAE-20基础油混合的固体润滑剂MoS_2的浓度百分比。实验是使用两级全因子设计概念进行的,而ANOVA技术已被用于验证数学模型的适当性。发现切削速度(V)在表面粗糙度和工具磨损方面起主要作用。进行敏感性分析以研究输入参数对响应的敏感性。

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