Evaluation of Electrical Discharge Machining Performance on Al (6351)–SiC–B4C Composite

Evaluation of Electrical Discharge Machining Performance on Al (6351)–SiC–B4C Composite

Uthayakumar M. (Kalasalingam University, India), Suresh Kumar S. (Kalasalingam University, India), Thirumalai Kumaran S. (Kalasalingam University, India) and Parameswaran P. (IGCAR, India)
Copyright: © 2019 |Pages: 16
DOI: 10.4018/978-1-5225-6161-3.ch005

Abstract

Electrical discharge machining (EDM) process is a non-conventional machining process used for the material which are difficult to machine. In this research work, an attempt has been made to determine the influence of Boron Carbide (B4C) particles on the machinablity of the Al (6351) alloy reinforced with 5 wt. % Silicon Carbide (SiC) Metal Matrix Composite (MMC) through EDM. Influence of machining parameters such as pulse current (I), pulse on time (Ton), duty factor (τ), and gap voltage (V) on affecting the output performance characteristics namely Electrode Wear Ratio (EWR), Surface Roughness (SR) and Power Consumption (PC) which are studied. The result shows that the addition of B4C particles significantly affects the machinablity of the composite, with a contribution of 1.6% on EWR, 3.5% on SR and 19.8% on PC. The crater, recast layer formation, and Heat Affected Zone (HAZ) in the machined surface of the composite are also reported in detail.
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Introduction

The metal matrix composites are having superior properties such as low density, high strength, light weight, lower thermal coefficient of expansion and good wear resistance. These materials are used in the various fields like aerospace, structural and automotive Industries (Ho & Newman, 2003). The recent research activity in MMC and its applications have been moved towards aluminum and aluminum alloy-based MMCs (Lindroos & Talvitie, 1995). The Aluminum metal matrix composites have wide application in the field of automotive engineering such as cylinder liner, piston and drive shaft and also in aerospace structure (Garg et al., 2010). The suitable fabrication method for MMCs is stir casting process since; this route is less expensive and appropriate to mass production (Kalaiselvan et al., 2011). However, aluminum metal matrix composites are hindered by high tool wear and poor machinability from the traditional machining process (Müller & Monaghan, 2000). Thus the non-conventional machining process like EDM is employed successfully to machine aluminum metal matrix composites (Taha, 2001). EDM is suitable to machine a composite material irrespective of their chemical and physical properties, but only applicable for electrically good conductor (Gopala Krishna & Prasad, 2009). Selection of EDM machining parameter is a difficult task, in order to improve the machining responses to achieve the requirements. The major response characteristics of electrical discharge machining process are surface roughness, electrode wear ratio and power consumption. In order to minimize product and process costs, the tool wear rate should be minimized with less effort. The optimal selection of input parameter is required to minimize the tool wear rate and maximize the material removal rate which in turn reduces the electrode wear ratio (Caroline et al., 2000). Rahman et al., (2010) have identified the influence of each input parameters with an aim to increase the metal removal while machining titanium alloy through EDM and concluded that the significant parameters are current and spark duration. Singh et al. (2012) have done machining on D3 tool steel by using die-sinking EDM with either copper or brass electrodes in kerosene dielectric. They found that a copper produced MRR at three times more than that when using an equivalent brass electrode. The on-time contributed to higher MRR significantly, but off-time had a less drastic change in MRR. Sultan et al. (2014) have reported the results of EDM on EN353 steel workpiece using copper tube electrode. Box-Behnken design was used for an experimental planning and they presented the results that MRR to be dependent not only on both peak current and on-time, but also off-time. Nur Seril et al., (2016) had attempted to predict material removal rate of different material using die sinking EDM process. The developed MRR model includes the EDM cumulative electrical charge for each cycle and melting temperature of workpiece material; it predicts two orders of magnitude closer to experimental data compared to a published model that is based on melting temperature and peak current alone.

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