Optimization of Machining Parameters on Tool Wear Rate of Ti-6Al-4V through EDM Using Copper Tungsten Electrode: A Statistical Approach

Rahman, M. M.; Khan, Md. Ashikur Rahman; Kadirgama, K.; Noor, M. M.; Bakar, Rosli Abu

doi:10.4028/www.scientific.net/amr.152-153.1595

Cited by 17 publications

(7 citation statements)

References 15 publications

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“…Laser ablation, polishing with diamond suspensions or cutting with diamond tools can be used to process non-conductive ceramics. But these processes are very expensive and time consuming [2][3][4][5]. Electrical discharge machining (EDM) is a machining process whereby a desired shape is obtained using electro-thermal energy.…”

Section: Introductionmentioning

confidence: 99%

INVESTIGATION OF THE MACHINABILITY OF NON-CONDUCTIVE ZrO2 WITH DIFFERENT TOOL ELECTRODES IN EDM

Moudood

Sabur

Lutfi

et al. 2014

Int. J. Automot. Mech. Eng.

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Electrical discharge machining (EDM) is a non-conventional process where complex and difficult-to-cut materials can be machined. Adhesive copper foil as an assisting electrode (AE) is used to cover the zirconia (ZrO 2 ) surface to start the primary spark between the tool electrode and workpiece. Kerosene is dissociated and produces a carbon layer on the workpiece surface when machining of the initial copper foil is completed. Thus machining continues although ZrO 2 is a non-conductive material. In this study, the EDM of ZrO 2 is investigated with graphite, copper and brass tool electrodes. Material removal rate (MRR) and surface characteristics are analysed. Experiments are performed by varying the parameters peak current and pulse-on time with different tool electrodes. From the experiments, MRR on ZrO 2 has been compared for three different tool electrodes. It is found that the graphite tool electrode performs the highest MRR for EDM of ZrO 2 . The least MRR is obtained by the brass tool electrode. However, better surface quality is observed with the copper tool electrode than EDM with brass or graphite electrodes. This investigation with varying machining parameters and different tool electrodes can be helpful in finding an effective use of the EDM process.

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Section: Introductionmentioning

confidence: 99%

INVESTIGATION OF THE MACHINABILITY OF NON-CONDUCTIVE ZrO2 WITH DIFFERENT TOOL ELECTRODES IN EDM

Moudood

Sabur

Lutfi

et al. 2014

Int. J. Automot. Mech. Eng.

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show abstract

“…Statistical experimental designs (response surface designs (RSM)) are most widely used in optimization experiments (Box & Draper, 1987;Khan et al, 2012a;Rahman, Khan, Kadirgama, Noor, & Bakar, 2010). The central composite design (CCD) is the most popular of the many classes of RSM designs due to the following three properties (Rahman, Khan, Kadirgama, Noor, & Bakar, 2011b …”

Section: Design Of Experimentsmentioning

confidence: 99%

Artificial Neural Network Modeling of Grinding of Ductile Cast Iron using Water Based SiO2 Nanocoolant

Rahman¹,

Kadirgama²,

Salwani³

2014

Int J Automot Mech Eng

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This paper presents optimization of the grinding progress of ductile cast iron using water-based SiO 2 nanocoolant. Conventional and water-based nanocoolant grinding was performed using a precision surface grinding machine. The study is aimed to investigate the effect of table speed and depth of cut on the surface roughness and material removal rate (MRR). Mathematical modeling is developed using the response surface method. An artificial neural network model is developed for predicting the surface roughness and MRR. Multi-layer perception and a batch back propagation algorithm are used. MLP is a gradient descent technique to minimize the error through a particular training pattern in which it adjusts the weight by a small amount at a time. From the experiment, the depth of cut is directly proportional to the surface roughness, but the table speed is inversely proportional to the surface roughness. The higher the value of the depth of cut, the lower the value of MRR, and vice versa for the table speed. It is concluded that the surface quality together with the material removal rate are the most affected by the depth of cut(s) and table speed.

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“…It is observed for same process parameter combination, different roughness values are obtained due to change in the material property [26][27][28]. The effect of process parameters, like pulse duration, pulse-off time, open circuit voltage, servo feed, servo voltage, dielectric flushing pressure, wire feed, and wire tension on surface roughness of Ti6Al4V material [29][30][31], AISI 4140 steel material [14], and AISI D2 tool steel material [32] were studied. It was found that roughness of Ti6Al4V was significantly affected by servo voltage, wire feed, and wire tension whereas the effect of open circuit voltage was dominant in machining AISI 1040 steel material.…”

Section: Effect Of Process Parametersmentioning

confidence: 99%

A progress review in wire electrical discharge machining process

Balan¹,

Giridharan²

2017

Int. J. Automot. Mech. Eng.

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Wire Electrical Discharge Machining (WEDM) is an electrothermal non-traditional machining process used for machining electrically conductive materials that are difficult to machine. Material removal in WEDM is by means of spark erosion. WEDM is proven to be the alternative for producing complex parts with higher degree of dimensional accuracy and better surface finish. Over the years, a significant amount of research was globally carried out to explore the WEDM process capability. This paper aims to explore the research work carried on parametric influence of WEDM process variables on various output performance measures. The paper also highlights various modelling techniques to predict optimal machining conditions and explore the feasibility of applying WEDM process to machine advanced materials. Combined technology that benefits from the virtues of WEDM and conventional method is also highlighted in this paper. The final section discusses the development and possible research trend in WEDM process.

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Optimization of Machining Parameters on Tool Wear Rate of Ti-6Al-4V through EDM Using Copper Tungsten Electrode: A Statistical Approach

Cited by 17 publications

References 15 publications

INVESTIGATION OF THE MACHINABILITY OF NON-CONDUCTIVE ZrO2 WITH DIFFERENT TOOL ELECTRODES IN EDM

INVESTIGATION OF THE MACHINABILITY OF NON-CONDUCTIVE ZrO2 WITH DIFFERENT TOOL ELECTRODES IN EDM

Artificial Neural Network Modeling of Grinding of Ductile Cast Iron using Water Based SiO2 Nanocoolant

A progress review in wire electrical discharge machining process

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