针对 Aa6061 数控铣削加工参数优化的 taguchi 和 promethee 整合研究

Muhammad Alif Ihsan, Y. Sumantri, Y. Irawan
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摘要

在制造业中,从使用传统机床到使用非常规机床,机械加工的发展相当迅速。如今经常使用的非常规机床是优化计算机数控(CNC)机床,在制造业中使用 CNC 能为产品质量和生产率带来许多好处。数控铣床就是其中之一,它是生产车间的主要机床之一。为了生产出具有良好、稳定质量和生产率的产品,加工优化成为实现理想响应的主要目标。表面质量由表面粗糙度决定,而生产率则由材料去除率决定。本研究旨在采用田口试验设计和偏好排序组织法(PROMETHEE)对 AA6061 的数控铣削加工参数进行优化。采用湿加工条件控制加工,以保持加工过程中的温度。实验共进行了九次,有三个因素和水平。这些因素包括主轴转速、进给量和切削深度。 研究结果表明,表面粗糙度和材料燃烧率组合的理想值为 0.565(实验 3)。这个最佳实验受主轴转速 2600 转/分钟、进给速度 65 毫米/分钟和切削深度 2.5 毫米的影响。进给速率对响应的影响最大,占 43.23%,其次是切削深度 25.24%,主轴转速 15.91%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
INTEGRATION OF TAGUCHI AND PROMETHEE FOR CNC MILLING MACHINING PARAMETER OPTIMIZATION ON AA6061
In the manufacturing industry, machining has developed quite rapidly from the use of conventional machines to unconventional machines. Unconventional machines that are often used today are optimize computer numerically controlled (CNC), the use of CNC in the manufacturing industry provides many benefits in product quality and productivity. One of them is CNC milling, this type is one of the main machines on the production floor. Machining optimization becomes the main goal to achieve the ideal response in order to produce products with good and consistent quality and productivity. Surface quality leads to surface roughness, while productivity leads to material removal rate. This study aims to optimize CNC milling machining parameters on AA6061 with Taguchi experimental design and preference ranking organization method for enrichment evaluation (PROMETHEE) method. Machining was controlled using wet machining conditions to maintain temperature during machining. Experiments were conducted nine times with three factors and levels. These factors included spindle speed, feed rate, and depth of cut.  The result of this research is the ideal value of the combination of surface roughness and material burning rate which is 0.565 (experiment 3). This best experiment is influenced by spindle speed 2600 rpm, feed rate 65 mm/min, and depth of cut 2.5 mm. Feed rate has the largest contribution in influencing the response which is 43.23%, followed by depth of cut 25.24%, and spindle speed 15.91%.
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