Influence of surfactant and graphite powder concentration on electrical discharge machining of PH17-4 stainless steel

被引:31
|
作者
Reddy, V. Vikram [1 ]
Kumar, A. [2 ]
Valli, P. Madar [3 ]
Reddy, Ch Sridhar [4 ]
机构
[1] Jayamukhi Inst Technol Sci, Dept Mech Engn, Warangal 506331, Andhra Pradesh, India
[2] NIT, Dept Mech Engn, Warangal, Andhra Pradesh, India
[3] GITAM Inst Technol, Dept Ind Engn, Visakhapatnam, Andhra Pradesh, India
[4] JNTU, Dept Mech Engn, Karimnagar, AP, India
关键词
EDM; Surfactant; Graphite powder; Material removal rate; Surface roughness; White layer thickness; Surface crack density; MATERIAL REMOVAL RATE; EDM PROCESS; PARAMETERS; SILICON; ROTARY; COPPER;
D O I
10.1007/s40430-014-0193-4
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
In the present work, an investigation has been made into the electrical discharge machining process (EDM) when both graphite powder and surfactant-mixed dielectric fluid were used during EDM of precipitation hardening stainless steel PH17-4. The addition of graphite powder in the dielectric fluid results in uniform distribution of discharge, which improves surface finish. However, agglomeration of graphite particles is found in the dielectric due to the electrostatic forces among the graphite powder particles. The addition of surfactant in the dielectric increases dielectric conductivity and in turn reduces relay time of discharge. This increases actual discharge time, which results in more material removal. At the same time, uniform distribution of graphite powder particles in the dielectric fluid is achieved. This leads to increase in discharge frequency, which results in increase in material removal rate and surface finish. Taguchi parameter design approach was used to get an optimal parametric setting of EDM process parameters namely: peak current, surfactant concentration and graphite powder concentration that yields to optimal process performance characteristics such as material removal rate, surface roughness, white layer thickness and surface crack density. Individual effect of process parameters on performance characteristics was also studied. To identify the significance of parameters on measured response, the analysis of variance has been carried out. Further, mathematical models were developed by performing nonlinear regression analysis to predict process performance characteristics. Confirmation tests were conducted at their respective optimal parametric settings to verify the predicted optimal values of performance characteristics.
引用
收藏
页码:641 / 655
页数:15
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