Multi-Objectives Optimization of Abrasive Water Jet Machining (AJWM) on Mild Steel

被引:0
作者
Halim, Nurul Hayati Abdul [1 ]
Tharazi, Izdihar [1 ]
Salleh, Farrahshaida Mohd [1 ]
Morni, Mohd Firhan [1 ]
Khalit, Muhammad Ilham [2 ]
Abdullah, Muhammad Azri Arifin [1 ]
机构
[1] Univ Teknol MARA, Coll Engn, Sch Mech Engn, Shah Alam 40450, Bahrain
[2] Bahrain Polytech, Sch Engn, Dept Mech Engn, Isa Town 33349, Bahrain
来源
INTERNATIONAL JOURNAL OF INTEGRATED ENGINEERING | 2024年 / 16卷 / 05期
关键词
Abrasive water jet; full factorial; ANOVA; optimization; SURFACE-ROUGHNESS; PARAMETERS;
D O I
10.30880/ijie.2024.16.05.015
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Abrasive waterjet machining (AWJM) is an advanced machining technology that is commonly used to machine hard materials that are difficult to machine using traditional methods. AWJM with a narrow stream of high-velocity water and abrasive particles offers a low-cost and environmentally friendly machining approach with a high rate of material removal. Some issues that were usually highlighted while cutting the metal are poor appearance cutting due to visible stream lagging particularly when working at high-speed cutting. This can lead to decreased accuracy and precision in the cutting process. Past literatures are mostly focused on improving the machining performances through intensive experimental works, thereby not many studies are concerned on process optimization through design of experiment approach. In this regard, this study aims to statically analyze how the controlled machining factors; transverse speed and cutting geometry influence surface roughness, and dimensional accuracy of a mild steel plate under the AWJC process. A two level Full Factorial method was applied to design the experiment that entailed 6 sets of parameters. Through the Analysis of Variance (ANOVA) on the experimental results, it was found that the dimensional accuracy are significantly influenced by the changes of cutting geometry. The factor also interacts with transverse speed to affect surface roughness. For optimization, the ANOVA suggest a transverse speed of 40% as the optimum value to produce a surface at 2.85 mu m of roughness and a dimension accuracy of 0.177% for the circular geometry-controlled factor.
引用
收藏
页码:187 / 200
页数:14
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