The Effect of Electrical Discharge Machining Parameters On 2024 Aluminum-Based Composite Material Using Calculation and Analysis of the Total Normalized Quality Loss and Signal-to-Noise Analysis

Subject Areas :

Behnam Masoudi ¹ , saeed daneshmand ²

1 - کارشناس ارشد مکانیک ساخت و تولید، اصفهان، دانشگاه آزاد اسلامی واحد خمینی شهر، دانشکده فنی و مهندسی
2 - دانشگاه آزاد اسلامی،واحد شهر مجلسی،دانشگاه مهندسی مکانیک، اصفهان، ایران

Received: 2016-09-24 Accepted : 2017-06-13 Published : 2017-05-22

Keywords: Optimization, Electrical discharge machining, ANOVA, Signal to Noise Ratio (S/N), 2024 Aluminum-Based Composite Material,

Abstract :

Metal matrix composites, according to the type of reinforcement used, have a different machinability. 2024 Aluminum matrix composites reinforced with aluminum oxide is among the materials the machining of which through traditional methods leads to the rapid wear of the tool; hence, EDM is a suitable method for machining this class of materials. Given that this machining method has different parameters, optimal set of machining parameters has a major effect on machining time, surface quality and tool wear rate. Using calculation and analysis of the total normalized quality loss (TNQL) and simultaneous signal to noise ratio of the outputs, this research is an attempt to investigate the effect of EDM parameters including current intensity, voltage, pulse on-time, and pulse off-time on material removal rate, tool wear rate and surface roughness in a the states of with and without powder and rotary tool. The results showed that current intensity and then pulse on-time, pulse off-time, and voltage have respectively the most important effect on output parameters of machining. The use of aluminum oxide powder and rotary tool increases gap and creates a centrifugal force and hence moves particles away from the area of machining and finally increases MRR. The use of aluminum powder in collision with sparks makes the sparks smaller and reduces their penetration depth and, thus, reduces the surface roughness. The results of optimization without powder and rotary tool proposes the combination of parameters as A3B1C2D3 while with powder and rotary tool proposes the combination of parameters as A1B1C2D3.

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