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首页> 外文期刊>The International Journal of Advanced Manufacturing Technology >Determination of optimum parameters for multi-performance characteristics in turning by using grey relational analysis
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Determination of optimum parameters for multi-performance characteristics in turning by using grey relational analysis

机译:基于灰色关联分析的车削综合性能最优参数确定

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摘要

Optimization of multi-criteria problems is a great need of producers to produce precision parts with low costs. Optimization of multi-performance characteristics is more complex compared to optimization of single-performance characteristics. The theory of grey system is a new technique for performing prediction, relational analysis, and decision making in many areas. In this paper, the use of grey relational analysis for optimizing the turning process parameters for the workpiece surface roughness and the chip thickness is introduced. Various turning parameters, such as cutting speed, feed rate, tool nose radius, and concentration of solid–liquid lubricants (minimum-quantity lubricant) were considered. A factorial design with eight added center points was used for the experimental design. Optimal machining parameters were determined by the grey relational grade obtained from the grey relational analysis for multi-performance characteristics (the surface roughness and the chip thickness). The results of confirmation experiments reveal that grey relational analysis coupled with factorial design can effectively be used to obtain the optimal combination of turning parameters. Experimental results have shown that the surface roughness and the chip thickness in the turning process can be improved effectively through the new approach. The minimum surface roughness and smallest chip thickness are 9.83 and 0.32 mm, respectively, obtained at optimal conditions of cutting speed, 1,200 rpm; feed rate, 0.06 mm/rev; nose radius, 0.8 mm; and concentration of solid–liquid lubricant (10% boric acid + SAE-40 base oil).
机译:生产商迫切需要优化多准则问题,以低成本生产精密零件。与单性能特征的优化相比,多性能特征的优化更为复杂。灰色系统理论是在许多领域中进行预测,关系分析和决策的新技术。本文介绍了利用灰色关联分析来优化车削表面粗糙度和切屑厚度的车削工艺参数。考虑了各种车削参数,例如切削速度,进给速度,刀尖半径和固液润滑剂(最小量润滑剂)的浓度。实验设计使用了具有八个附加中心点的析因设计。最佳加工参数由灰色关联等级确定,该等级是从灰色关联分析获得的,用于多种性能特征(表面粗糙度和切屑厚度)。确认实验的结果表明,灰色关联分析与因子设计相结合可以有效地获得车削参数的最佳组合。实验结果表明,采用这种新方法可以有效改善车削过程中的表面粗糙度和切屑厚度。在最佳转速(1200 rpm)下获得的最小表面粗糙度和最小切屑厚度分别为9.83和0.32 mm。进给速度0.06 mm / rev;鼻子半径0.8毫米;固液润滑剂的浓度(10%硼酸+ SAE-40基础油)。

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