A multi-criteria decision-making in relieving grinding process of surface of gear milling tooth based on the archimedean spiral using taguchi-ahp-topsis method

Q3 Engineering
Kien Huy Nguyen, D. V. Pham, Quoc Ve Tran
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引用次数: 0

Abstract

In this study, in order to optimize the quality criteria of the machined surface based on the Archimedean spiral, the relieving grinding process (RGP) was performed to machine the material of HSS P18 in a 1Б811 machine with four input parameters including graininess of grinding wheel (G), grinding wheel hardness (Hd), velocity of grinding wheel (V), and feed rate (s) and with three quality criteria including surface roughness (Ra), hardening of surface layer (∆HRC), and hardened layer thickness (∆L). Taguchi-AHP-Topsis method was successfully applied to solve the Multi-Criteria Decision Making (MCDM) problem in this case. The optimized results of the output parameters are surface roughness of 0.21 µm, surface hardening of 1.45 HRC, and hardened layer thickness of 34.18 µm. These results were determined at the set of the input parameters includes G, V, s with their values of 120, 24 m/s, 2.08 m/min, respectively, and Hd at level 1. The optimal results were verified through the comparison between the calculated and the experimental results using this set of optimal parameters. The differences between the calculated results and the experimental results were quite small (maximum different value was 4.8 %) Thus, the results of this study can be applied to solve the multi-objective optimization problems in RGP of the GMT surface based on the Archimedean spiral
基于阿基米德螺旋的齿轮铣削齿面解磨工艺的多准则决策
为了优化基于阿基米德螺旋的加工表面质量标准,以砂轮粒度(G)、砂轮硬度(Hd)、砂轮速度(V)和进给速度(s) 4个输入参数,以表面粗糙度(Ra)、表层硬化(∆HRC)、硬化层厚度(∆L)。应用田口ahp - topsis方法成功地解决了该案例中的多准则决策问题。输出参数优化后的表面粗糙度为0.21µm,表面硬化度为1.45 HRC,硬化层厚度为34.18µm。这些结果是在输入参数G, V, s分别为120,24 m/s, 2.08 m/min和1级Hd时确定的。利用这组最优参数,将计算结果与实验结果进行比较,验证了最优结果。计算结果与实验结果的差异很小(最大差异为4.8%),因此,本研究结果可用于解决基于阿基米德螺旋的GMT曲面RGP的多目标优化问题
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
EUREKA: Physics and Engineering
EUREKA: Physics and Engineering Engineering-Engineering (all)
CiteScore
1.90
自引率
0.00%
发文量
78
审稿时长
12 weeks
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