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首页> 外文期刊>Materials and Manufacturing Processes >Machining Parameters Optimization of Titanium Alloy using Response Surface Methodology and Particle Swarm Optimization under Minimum-Quantity Lubrication Environment
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Machining Parameters Optimization of Titanium Alloy using Response Surface Methodology and Particle Swarm Optimization under Minimum-Quantity Lubrication Environment

机译：最小量润滑环境下响应面法和粒子群算法优化钛合金加工参数

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摘要

The present paper depicts an application of response surface methodology (RSM) and particle swarm optimization (PSO) technique for optimizing the machining factors in turning of titanium (Grade-II) alloy using cubic boron nitride insert tool under minimum quantity lubricant (MQL) environment. The three machining factors, i.e., cutting speed (V-c), feed rate (f) and side cutting edge angle (approach angle ), are designed as three factors by using RSM design, which is withal subject to several constraints including tangential force (F-c), tool wear (V-Bmax), surface roughness (R-a) and tool-chip contact length (L). The multiple regression technique was used to establish the interaction between input parameters and given responses. Moreover, the results have been presented and optimized process parameters are acquired through multi-response optimization via desirability function as well as the PSO technique. The lower values of V-c (200m/min), f (0.10mm/rev) and higher values of phi (90 degrees) are the optimum machining factors for minimizing the aforementioned responses. It was also observed that the selected responses predicated on PSO are much closer as that of the values acquired in view of the desirability function approach. Henceforth, PSO has the potential to cull appropriate machining factors while turning titanium (Grade-II) alloys under MQL conditions.
机译：本文描述了应用响应表面方法（RSM）和粒子群优化（PSO）技术优化在最小量润滑剂（MQL）环境下使用立方氮化硼插入工具进行钛（Grade-II）合金车削的加工因子的应用。 。通过使用RSM设计，将切削速度（Vc），进给速度（f）和侧面切削刃角度（接近角）这三个加工因素设计为三个因素，这会受到包括切向力（Fc）在内的一些约束。 ），刀具磨损（V-Bmax），表面粗糙度（Ra）和刀具与切屑的接触长度（L）。多元回归技术被用来建立输入参数和给定响应之间的相互作用。此外，已经提出了结果，并通过期望函数和PSO技术通过多响应优化获得了优化的工艺参数。 V-c（200m / min），f（0.10mm / rev）的较低值和phi（90度）的较高值是使上述响应最小化的最佳加工因子。还观察到，基于期望函数方法，基于PSO的所选响应与获取值的响应更加接近。今后，PSO可能会在MQL条件下车削钛（II级）合金时剔除适当的加工因子。

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