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The fuzzy inference system approach to a multi-performance characteristic index for surface quality improvement in CNC end milling

机译:多功能性能指标的模糊推理系统方法,用于改善数控立铣刀的表面质量

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Utility embedded fuzzy approach has been adopted for multiple surface quality optimisation of 6061 T4 Aluminium in CNC end milling operation. The purpose is to evaluate the most favourable process environment consisting of selected process parameters viz. spindle speed, feed and depth of cut in order to satisfy multiple requirements of surface integrity. Various surface roughness parameters have been taken into account with a focus to minimise all of them simultaneously. Utility concept has been adopted to convert individual surface roughness parameters into corresponding utility value which have been fed to a fuzzy inference system to obtain a multi-performance characteristic index (MPCI). MPCI has been optimised finally using Taguchi method. Detailed methodology of the proposed approach has been presented with an illustrative example followed by satisfactory result of confirmatory test.
机译:在数控立铣刀操作中,采用了实用的嵌入式模糊方法对6061 T4铝的多个表面质量进行了优化。目的是评估由所选过程参数viz组成的最有利的过程环境。主轴转速,进给量和切削深度,以满足表面完整性的多种要求。考虑了各种表面粗糙度参数,重点是使所有这些参数同时最小化。已采用效用概念将各个表面粗糙度参数转换为相应的效用值,这些参数已输入到模糊推理系统中以获得多功能性能指标(MPCI)。最后,使用田口方法对MPCI进行了优化。提出的方法的详细方法已经给出了说明性的例子,随后是验证测试的令人满意的结果。

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