Electrical Discharge Machining (EDM) Characteristics Associated with Electrical Discharge Energy on Machining of Cemented Tungsten Carbide

In this investigation, cemented tungsten carbides graded K10 and P10 were machined by electrical discharge machining (EDM) using an electrolytic copper electrode. The machining parameters of EDM were varied to explore the effects of electrical discharge energy on the machining characteristics, such as material removal rate (MRR), electrode wear rate (EWR), and surface roughness. Moreover, the effects of the electrical discharge energy on heat-affected layers, surface cracks and machining debris were also determined. The experimental results show that the MRR increased with the density of the electrical discharge energy; the EWR and diameter of the machining debris were also related to the density of the electrical discharge energy. When the amount of electrical discharge energy was set to a high level, serious surface cracks on the machined surface of the cemented tungsten carbides caused by EDM were evident.     

Study of the Effect of Machining Parameters on the Machining Characteristics in Electrical Discharge Machining of Fe-Mn-Al Alloy

In this work we investigated the electrical discharge machining (EDM) of a Fe-Mn-Al alloy. The surface phenomena caused by EDM were studied in terms of machining parameters. An empirical model of the Fe-Mn-Al alloy was also proposed based on the experimental data. Experimental results indicate that the higher the discharge energy, the faster the machining time. This treatment introduces machining damage in the resolidified surface layer and worsens the surface roughness. The optimum pulse-on duration on the basis of the electrode wear ratio for the copper electrode was about 200 μs. The increase of crater depth with the applied pulsed current and pulse-on duration appears minimal under a small input energy.     

Machining Characteristics and Optimization of Machining Parameters of SKH 57 High-Speed Steel Using Electrical-Discharge Machining Based on Taguchi Method

The effects of the machining parameters in electrical-discharge machining (EDM) on the machining characteristics of SKH 57 high-speed steel were investigated. A well-designed experimental scheme was used to reduce the total number of experiments. Parts of the experiment were conducted with the L18 orthogonal array based on the Taguchi method. Moreover, the signal-to-noise ratios associated with the observed values in the experiments were determined by ANOVA and F-test. The significant parameters that critically influenced the machining characteristics were examined, and the optimal combination levels of machining parameters for material removal rate, electrode wear rate, and surface roughness were determined.     

Investigation into the Effect of Voltage Excitation of Pre-Ignition Spark Pulse on the Electro-Discharge Machining (EDM) Process

Studying the variation of the electro-discharge machining (EDM) process outputs due to the change in shape of the generated pulse is one research aspect in the EDM process. In this study, the effects of voltage excitation of the pre-ignition spark pulse on the process outputs material removal rate (MRR), electrode wear ratio (EWR), and surface roughness (Ra) have been investigated. Experiments were designed using design of experiments (DOE), and the results were analyzed using analysis of variance (ANOVA). Based on the results, it has become clear that applying voltage excitation of the pulse produces effective pulses, which in turn lessens EWR, increases MRR, and improves surface quality. Hence, the suitability of this method has been verified for EDM.     

An Experimental Study on Electrical Discharge Machining of Manganese-Zinc Ferrite Magnetic Material

The objective of this research is to investigate the machining characteristics of manganese-zinc (Mn-Zn) ferrite magnetic material using electrical-discharge machining (EDM). The material removal rate, the surface topography, the surface roughness, the recast layer, and the chemical composition of the machined surface were studied in terms of EDM processing variables. Experimental results indicate that the morphology of debris revealed the mechanism of material removal. The surface microgeometry characteristics are not always uniform and homogenous and the EDM process produces much damage on the machined surface. The material removal rate, the surface roughness, and the recast layer are proportional to the applied discharge energy.     

Multiple Performance Optimization of Machining Parameters on the Machining of GFRP Composites Using Carbide (K10) Tool

The present investigation focuses on the multiple performance machining characteristics of GFRP composites produced through filament winding. Grey relational analysis was used for the optimization of the machining parameters on machining GFRP composites using carbide (K10) tool. According to the Taguchi quality concept, a L27, 3-level orthogonal array was chosen for the experiments. The machining parameters namely work piece fiber orientation, cutting speed, feed rate, depth of cut and machining time have been optimized based on the multiple performance characteristics including material removal rate, tool wear, surface roughness and specific cutting pressure. Experimental results have shown that machining performance in the composite machining process can be improved effectively by using this approach.     

Process Optimization of Finish Turning of Hardened Steels

Process planning and optimization is crucial to help establish the economic and quality viability of hard turning processes with the presence of a wide spectrum of tooling and process parameters. A systematic methodology is discussed in this paper to design the optimal tool geometry and cutting conditions for hard turning, incorporating the consideration of part finish, tool wear, and material removal rate. Experimental demonstration of the optimization scheme is presented at two levels: the first level is to validate the process prediction results and the second is to validate the optimization results. Hardened AISI 1053 steel was selected as the workpiece material in this study and its material property related parameters, including the Johnson-Cook constants and wear coefficients, were determined based on the machining tests. It is seen that the cutting force and tool wear progression agrees well with the predictions from 3-D oblique cutting model, and the machined surface roughness can be predicted with a surface kinematic model incorporating the plowing effect. The experimental results also showed that the process configuration as derived from the analytical optimization procedure lends itself to superior results in comparison to other experimental results under non-optimal configurations.     

Modeling and Analysis of Machinability Evaluation in the Wire Electrical Discharge Machining (WEDM) Process of Aluminum Oxide-Based Ceramic

The wire electrical discharge machining (WEDM) allowed success in the manufacture of the hard, fragile, and materials difficult to cut, especially for electroconductive ceramic materials. In this study, the mathematical models of material removal rate (MRR) and surface roughness (SR) used for the machinability evaluation in the WEDM process of aluminum oxide-based ceramic material (Al₂O₃ + TiC) have been carried out. The experimental plan adopts the face centered central composite design (CCD). The mathematical models using the response surface methodology (RSM) are developed so as to investigate the influences of four machining parameters, including the peak current, pulse on time, duty factor, and wire speed, on the performance characteristics of MRR and SR. It has been proved that the proposed mathematical models in this study would fit and predict values of the performance characteristics, which would be close to the readings recorded in experiment with a 95% confidence level. The significant parameters that critically affect the performance characteristics are examined.     

Optimization of Polishing Parameters with Taguchi Method for LBO Crystal in CMP

Chemical mechanical polishing(CMP)was used to polish Lithium triborate(LiB3O5 or LBO)crystal.Taguchi method was applied for optimization of the polishing parameters.Material removal rate(MRR)and surface roughness are considered as criteria for the optimization.The polishing pressure,the abrasive concentration and the table velocity are important parameters which influence MRR and surface roughness in CMP of LBO crystal.Experiment results indicate that for MRR the polishing pressure is the most significant p...     

Characterization of Properties of Cryogenically Treated Al-SiC Composites Fabricated by Powder Metallurgy

The basis of this research was an exploration of the fundamental phenomena that determine the response of silicon carbide-reinforced aluminium composite material to thermal cycling between cryogenic and ambient temperatures. This analysis began with a phenomenological approach that investigated the role of the production, processing, and machining of composite materials, and led to study of their mechanical behavior at cryogenic temperatures. Electric discharge machining was done on the composite specimens and mathematical models were developed for predicting the machining parameters such as metal removal rate, tool wear rate, and surface roughness. A five-level factorial design was chosen for experimentation and mathematical models were developed using the software DOE-PC IV. An analysis of variance technique was used to calculate the regression coefficients and to check the significance of the models developed. This approach provided an understanding of how temperature and vol.% of SiC influence composite machining behavior. The hardness, wear resistance, and tensile property are high for cryo-treated specimens and these properties reduce with increase in temperature. The properties also increase with increasing % of SiC reinforcements. The microstructures of the wear specimens show worn-out layers and grooves formed in the debris. The cryo-treated and the higher reinforced specimens exhibit less material removal and tool wear rate and this increases with increase in temperature. There is a relatively higher surface roughness when there is greater material removal.     

Optimization of Dry Machining Parameters for High-Purity Graphite in End-Milling Process by Artificial Neural Networks: A Case Study

The machining factors affecting the tool wear and the surface roughness produced in the end-milling process are generally the cutting speed, the feed rate, the depth of cut, etc. This article focused on finding an optimal cutting parameter setting of high-purity graphite under dry machining conditions by an artificial neural network and the Sequential Quadratic Programming method [1 Fletcher , R. Practical methods of optimizations . Vol. 1, Unconstrained Optimization, and Vol. 2 Constrained Optimization ; John Wiley and Sons , 1981 . [Google Scholar]]. This algorithm yielded better performance than the traditional methods such as the Taguchi method and the Design of Experiments (DOE) approach. Additionally, the tool worn surfaces after machining were examined with tool electron microscopy (TEM) to observe the tool wear mechanisms.