RSM model to evaluate material removal rate in EDM of Ti-5Al-2.5Sn using graphite electrode

被引:1
|
作者
Khan, Md. Ashikur Rahman [1 ]
Rahman, M. M. [1 ]
Kadirgama, K. [1 ]
Ismail, A. R. [1 ]
机构
[1] Univ Malaysia Pahang, Fac Mech Engn, Pekan 26600, Pahang, Malaysia
关键词
DISCHARGE MACHINING PROCESS; NEURAL-NETWORK; OPTIMIZATION; PARAMETERS; TI-6AL-4V;
D O I
10.1088/1757-899X/36/1/012016
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
The usage of electrical discharge machining (EDM) is increasing gradually owing to its capability to cut precisely, geometrically complex material regardless hardness. Many process parameters greatly affect the EDM performance and complicated mechanism of the process result the lag of established theory. Hence, it becomes important to select the proper parameter set for different machining stages in order to promote efficiency. In view of these barriers, it is attempted to establish a model which can accurately predict the material removal rate (MRR) of titanium alloy by correlating the process parameter. Effect of the parameters on MRR is investigated as well. Experiment is conducted utilizing the graphite electrode maintaining negative polarity. Analysis and modelling is carried out based on design of experiment as well as response surface methodology. The agreeable accuracy is obtained and thus the model can become a precise tool setting the EDM process cost effective and efficient. Moreover, high ampere, short pulse-off time and low servo-voltage combined with about 250 mu s pulse-on time generate the highest MRR.
引用
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页数:9
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