Influence of process parameters in electrical discharge machining on H13 die steel

Bahgat, M.; Shash, Ahmed Y.; Abd-Rabou, M.; El-Mahallawi, I.

doi:10.1016/j.heliyon.2019.e01813

Cited by 28 publications

(14 citation statements)

References 8 publications

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“…This is because each material has a different composition. Thus, the selection of electrode material is important in this process (Bahgat et al, 2019). In the present research, the suitable electrode material for producing better surface roughness is graphite.…”

Section: Resultsmentioning

confidence: 91%

Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method

Rachman¹,

Purnomo²,

Fajardini³

et al. 2021

JTAM

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This research aims to obtain optimal value for the surface roughness of the material AISI P20 on the Electrical Discharge Machining (EDM) Sinking process. In the present research, the Taguchi method is used to investigate the signiﬁcant influence of process variables on the machining performance and determine the combination of process variables on the EDM process. Orthogonal array L18 (21 × 33) based on the Taguchi method is chosen for the design of experiment. The experiment is replicated twice to finding out the influence of four process variables such as type of electrode, voltage gap, on-time, and off-time on the response performance. Machining performance is evaluated by surface roughness as a response variable that had quality characteristics, smaller is better. These experimental data were analyzed using the Signal-to-noise ratio and Analysis of Variance. The analysis results show that the surface roughness is influenced by the type of electrode and on time. Combination of process variables to obtain optimal surface roughness are using graphite electrodes, and setting values of gap voltage 40 volt, on-time 250 μs, and off-time 20 μs. This combination of process variables can be applied to the manufacturing process using EDM sinking in order to produce a good quality product that determined based on the surface roughness value.

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Section: Resultsmentioning

confidence: 91%

Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method

Rachman¹,

Purnomo²,

Fajardini³

et al. 2021

JTAM

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show abstract

“…It was found that an increase in SR values was prompted by the large pulse on time. The brass electrode produced the best results for SR values [20]. For Monel superalloys, roughness values experienced a gradual increment with increment in the pulse on time.…”

Section: Surface Roughnessmentioning

confidence: 94%

“…Meanwhile, for brass electrode, an increment in current and time of pulse prompted a significant increment in MRR. It was also found that the copper electrode with a maximum current of 14A and 150µs pulse on-time gave the highest MRR[20].…”

mentioning

confidence: 89%

Tool Wear Rate Prediction by using Optimization Techniques

Kumaran,

Srinivasan,

et al. 2019

IJITEE

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Electro discharge machining is a non-traditional machining process used for machining hard-to-machine materials, such as various grades of titanium alloys, heat-treated alloy steels, composites, tungsten carbides, and so forth. These materials are hard to machine with customary machining procedures like drilling, milling and hence electro-discharge machining is used to machine such materials to get better quality and efficiency. These materials are generally utilized in current industries like die making industries, aeronautics, nuclear industries, and medical fields. This type of machining is thermalbased, and machining takes place due to repetitive electric sparks that generate between workpiece and tool. Both tools and workpieces are inundated in a dielectric liquid, which has two primary functions. In the first place, it behaves like a medium between the work metal and the tool. Second, it is a flushing agent to expel the machined metal from the machined zone. Machining parameters like a pulse on time, current, wire feed the tool and gap voltage affect the output responses like surface roughness and material removal rate. The material removal rate is a significant parameter that determines machining efficiency. Surface roughness is also a vital parameter that decides machining quality. A lot of research has been conducted to determine the optimum parameters for obtaining the best results. In the present work, a comprehensive review of different types of EDM and the effect of various machining parameters on the surface roughness, material removal rate, and other response parameters has been done.

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“…The control parameters were again the pulse-on current, time, and voltage, utilizing a Taguchi Design of Experiment (DOE), while additionally, they conducted experiments with reverse electrode polarity. The machining of H13 die steel using different electrode materials and for different pulse-on current and time was experimentally studied by Bahgat et al [ 15 ], while in the work of Rani et al [ 16 ], the improvement of metal removal efficiency through executing the amendment of electrical circuits in EDM for machining Eglin steel was discussed. The machining of Eglin steel with EDM was also studied by Sahayaraj et al [ 17 ] employing an Artificial Neural Network (ANN) model to predict the machining process results.…”

Section: Introductionmentioning

confidence: 99%

An Optimalization Study on the Surface Texture and Machining Parameters of 60CrMoV18-5 Steel by EDM

et al. 2022

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As a non-conventional machining technology, EDM is used extensively in modern industry, particularly in machining difficult-to-cut materials. CALMAX is a chromium-molybdenum-vanadium tool steel with exceptional toughness, ductility, and wear resistance that has a wide range of applications. Despite the fact that EDM is routinely used in CALMAX machining, the related published research is brief and limited. The current research gives a complete experimental study of CALMAX machining using EDM. A Taguchi Design of Experiment (DOE) was used, using pulse-on current, pulse-on time, and open-circuit voltage as control parameters. Material Removal Rate (MRR), Tool Material Removal Rate (TMRR), and Tool Wear Ratio (TWR) were used to evaluate machining performance, while Ra and Rz were used to estimate Surface Quality (SQ). The produced White Layer (WL) parameters were determined using optical and SEM microscopy, as well as EDX measurements and micro-hardness studies. Finally, for each of the aforementioned indexes, Analysis of Variance (ANOVA) was performed, and multi-objective optimization was based on Grey Relational Analysis (GRA). The results show that higher open-circuit voltage produces lower WL thickness, although by increasing the pulse-on time, the TWR is increased. The average hardness of the WL is increased about 400% compared to the micro-hardness of the bulk material.

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Influence of process parameters in electrical discharge machining on H13 die steel

Cited by 28 publications

References 8 publications

Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method

Optimization of Surface Roughness of AISI P20 on Electrical Discharge Machining Sinking Process using Taguchi Method

Tool Wear Rate Prediction by using Optimization Techniques

An Optimalization Study on the Surface Texture and Machining Parameters of 60CrMoV18-5 Steel by EDM

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