Multi-Objective Optimization of PMEDM Input Factors for Processing Cylindrical Shaped Parts

2021 ◽  
Vol 1018 ◽  
pp. 71-77
Author(s):  
Tran Thi Hong ◽  
Nguyen Van Cuong ◽  
Tran Ngoc Hien ◽  
Bui Thanh Danh ◽  
Le Hong Ky ◽  
...  
Keyword(s):  
Removal Rate ◽  
Electrode Wear ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Powder Concentration ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
The Impact ◽  
Optimum Input

The present work deals with multi-objective optimization of powder mixed electric discharge machining (PMEDM) when processing cylindrically shaped parts. In this work, the pulse on time Ton, the pulse off time Toff, the powder concentration Cp, the pulse current IP, and the server voltage SV were chosen for the optimization problem. Also, the surface roughness (SR), the material removal rate (MRR), and the electrode wear (EW) were chosen as three objectives for the investigation. Besides, the Taguchi method and the grey relational analysis (GRA) were applied for optimizing simultaneously three the SR, the MRR and the EW to find the optimum input factors. The impact of the process parameters on the overall goal was weighed. Additionally, optimum input factors of PMEDM process for multi-objectives were recommended.

scholarly journals Multi-Objective Optimization of Wire Electrical Discharge Machining of AL 2124/SIC Composite

2019 ◽  
Vol 9 (1) ◽  
pp. 2155-2163
Keyword(s):  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
High Strength ◽  
Wire Electrical Discharge Machining ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Predicted Values ◽  
Pulse On Time ◽  
Pulse Off Time

The growing demand for the use of high strength to weight alloys in industries for manufacturing complex structures challenges the machinability of such advanced materials. In the present investigation, the machinability of SiC particle reinforced Al 2124 composite was studied on Wire electrical discharge machining (WEDM). The process parameters namely pulse on-time (Ton), pulse off time (Toff), peak current (IP), and servo voltage (SV) were optimized by utilizing the central composite design layout. The output responses such as kerf and material removal rate (MRR) were studied in detail. The single and multi-objective optimization was studied for a combination effect using Derringer’s desirability approach and Genetic Algorithm (GA). The experimental and predicted values for each response were validated at the optimized condition. The experimental results were found in line with the predicted values. Multi objective optimization of kerf and MRR by GA showing better result compared to RSM.

Multi-Objective Optimization of Electrical Discharge Machining Parameters for 2024 Aluminum Alloy Using Grey-Taguchi Method

2020 ◽  
Vol 998 ◽  
pp. 55-60
Author(s):  
Jurapun Phimoolchat ◽  
Apiwat Muttamara
Keyword(s):  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
2024 Aluminum Alloy ◽  
Multi Objective ◽  
Effect Estimation ◽  
Voltage Performance ◽  
Pulse On Time

This paper focused on Grey relational analysis (GRA) to optimize EDM parameters through multi-objective optimization for Al2024 aluminum and electrode graphite ISO-63 was used as a cutting tool. The process parameters pulse on time, duty factor, pulse current and open voltage. Performance characteristics examined included material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). Taguchi’s 27 experimental designs, often called an orthogonal array (OA), was utilized to ignore interaction and concentrate on main effect estimation. GRA was performed to optimize input parameters levels. Results were that MRR increased from 35.00 to 35.11 mm3/min, EWR decreased from 11.63 to 10.89 mm3/min, and SR decreased from 5.01 to 4.97 μm. Taguchi and GRA resulted in clear improvements in MRR, EWR, and SR.

Multi-Response Optimization of EDM for Ti-6Al-4V Using Taguchi - Grey Relational Analysis

2017 ◽  
Vol 266 ◽  
pp. 43-50 ◽  
Author(s):  
Ritesh Joshi ◽  
Gopal Zinzala ◽  
Nishit Nirmal ◽  
Kishan Fuse
Keyword(s):  
Grey Relational Analysis ◽  
Removal Rate ◽  
Optimization Technique ◽  
High Strength ◽  
Operating Conditions ◽  
Electrode Wear ◽  
Relational Analysis ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time

Ti-6Al-4V is a titanium alloy having high strength, low weight and corrosion resistant which is a required characteristic for a material to be used in aerospace industry. Titanium, being a hard alloy is difficult to the machine via conventional methods so it is a call to use non-conventional processes. In present work, the effects on Ti-6Al-4V by drilling a hole of Ø 6 mm using copper (99%) electrode in electric discharge machining (EDM) process is analyzed. Experiments were performed under different operating conditions of peak current, pulse-on time and pulse-off time. Multi-objective optimization technique Grey relational analysis is used for process optimization of material removal rate (MRR) and electrode wear rate (EWR). Experiments are designed using an L9 orthogonal array. ANOVA is used for finding most contributing parameter followed by confirmation tests for validating the results.

Nature-Inspired Metaheuristic Approach for Multi-Objective Optimization During WEDM Process

2018 ◽  
pp. 91-122
Author(s):  
Goutam Kumar Bose ◽  
Pritam Pain
Keyword(s):  
Removal Rate ◽  
Experimental Result ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
The Individual ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Grey Relation ◽  
Off Time

In this research paper Wire-Electric Discharge Machining (WEDM) is applied to machine AISI-D3 material in order to measure the performance of multi-objective responses like high material removal rate and low roughness. This contradictory objective is accomplished by the control parameters like Pulse on Time (Ton), Pulse off Time (Toff), Wire Feed (W/Feed) and Wire Tension (W/Ten) employing brass wire. Here the orthogonal array is used to developed 625 parametric combinations. The optimization of the contradictory responses is carried out in a metaheuristic environment. Artificial Neural Network is employed to train and validate the experimental result. Primarily the individual responses are optimized by employing Firefly algorithm (FA). This is followed by a multi-objective optimization through Genetic algorithm (GA) approach. As the results obtained through GA infer a domain of solutions, therefore Grey Relation Analysis (GRA) is applied where the weights are considered through Fuzzy set theory to ascertain the best parametric combination amongst the set of feasible alternatives.

Parametric optimization in die-sinking EDM of Nimonic 90 alloy using Taguchi-based GRA approach

2020 ◽  
Vol 18 (1) ◽  
pp. 146-156
Author(s):  
Sahil Sharma ◽  
Umesh Kumar Vates ◽  
Amit Bansal
Keyword(s):  
Electric Discharge ◽  
Optimization Technique ◽  
Electrode Wear ◽  
Content Type ◽  
Response Characteristics ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
The Impact ◽  
Off Time

Purpose In the current exploration, the machining of a Nimonic 90 superalloy material was carried out in a die-sinking electric discharge machine. Experimentation was performed to investigate the impact of three input machining factors – current (I), pulse on time (Ton) and pulse off time (Toff) – on various response characteristics such as material removal rate (MRR), surface roughness (Ra) and electrode wear rate (EWR). Design/methodology/approach A Taguchi L9 design and ANOVA were used to assess machine response characteristics. The study also involved a grey relational analysis (GRA) multi-objective technique of optimization. Findings For single-objective performance, the most appropriate machining factors for achieving the best performance were attained as: MRR (I = 20 A, Ton = 200 µs and Toff = 45 µs), Ra (I = 14 A, Ton = 100 µs and Toff = 25 µs) and EWR (I = 17 A, Ton = 150 µs and Toff = 45 µs). The proposed grey relational approach provided the optimal settings (i.e. 14 A I, 100 µs Ton and 25 µs Toff) for the variables used to calculate the predicted and experimental results. Also, a confirmation test indicated that the final experimental grey relational grade value was enhanced when the experimentation was performed at optimal setting. Originality/value To the best of the authors’ knowledge, the present work is the first to examine the proposed machining variables (i.e. current, pulse on time and pulse off time) in relation to the optimization technique of GRA for a Nimonic 90 alloy using a die-sinking electric discharge machining method.

Effect of Input Parameters on Electrode Wear in PMEDM Cylindrical Shaped Parts

2020 ◽  
Vol 861 ◽  
pp. 136-142
Author(s):  
Le Hong Ky ◽  
Bui Thanh Danh ◽  
Nguyen Van Cuong ◽  
Tran Thi Hong ◽  
Thai Vinh Nguyen ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Electrode Wear ◽  
Workpiece Material ◽  
Powder Concentration ◽  
Alloy Tool ◽  
Input Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Optimum Input

This paper deals with the effect of input parameters of Powder Mixed Electric Discharge Machining (PMEDM) process on the surface roughness when processing cylindrical shaped parts. In this work, the workpiece material is 90CrSi alloy tool steel and the nanopowder is silicon carbide. Also, five input parameters including the pulse on time, the pulse off time, the powder concentration, the current and the server voltage were selected to investigate their influence on the surface roughness. Taguchi method and ANOVA analysis were used and the effect of input parameters on the surface roughness was presented. Moreover, optimum input parameters for minimum surface roughness was suggested.

scholarly journals Optimizing Main Process Parameters When Conducting Powder-Mixed Electrical Discharge Machining of Hardened 90CrSi

Machines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 375
Author(s):  
Anh-Tuan Nguyen ◽  
Xuan-Hung Le ◽  
Van-Tung Nguyen ◽  
Dang-Phong Phan ◽  
Quoc-Hoang Tran ◽  
...  
Keyword(s):  
Process Parameters ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Optimization Process ◽  
Main Process ◽  
Electrode Wear ◽  
Powder Concentration ◽  
Pulse On Time ◽  
Pulse Off Time

In the current study, an optimization process of powder-mixed electrical discharge machining (PMEDM) process when machining cylindrically shaped parts made of hardened 90CrSi steel is reported. In this study, SiC powder was mixed into the Diel MS 7000 dielectric solution. Additionally, graphite was chosen as the electrode material. The multi-objective functions were minimizing the surface roughness (SR) and electrode wear rate (EWR) and maximizing the material removal rate (MRR). The used input parameters of the optimization process included the powder concentration, the pulse-on time, the pulse-off time, the pulse current, and the servo voltage. A combination between the Taguchi method and the grey relation analysis (GRA) method with the support of Minitab R19 software was used to design the experiment and analyze the results. It was found that the optimal set of process parameters that can satisfy the above responses are Cp of 0.5 g/L, Ton of 8 µs, Toff of 8 µs, IP of 5 A, and SV of 4 V.

Optimization of Process Parameters for Silicon Carbide Powder Mixed EDM

2019 ◽  
pp. 55-81
Author(s):  
Sasmeeta Tripathy ◽  
Deba Kumar Tripathy
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Base Material ◽  
Carbide Powder ◽  
Electrode Wear ◽  
Powder Concentration ◽  
Optimization Of Process Parameters ◽  
Recast Layer Thickness ◽  
Grey Relational ◽  
Pulse On Time

The present chapter deals with the investigations on the effect of process parameters like powder concentration (Cp), peak current (Ip), pulse-on-time (Ton), duty cycle (DC), and gap voltage (Vg) on output responses like material removal rate (MRR), tool wear rate (TWR), electrode wear ratio (EWR), surface roughness (SR), recast layer thickness (RLT), and micro-hardness (HVN) for PMEDM of H-11 hot work tool steel. Multi-objective optimization using grey relational analysis (GRA) has been implemented to identify the optimum set of input parameters to achieve maximum MRR and HVN with minimum TWR, EWR, SR, and RLT at the same time. Predicted results on verification with confirmation tests improve the preference values by 0.09468 with GRA. The recommended settings of process parameters is found to be Cp=6g/l, Ip=3Amp, Ton=100µs, DC=70%, and Vg=30V from GRA. The microstructures were examined with scanning electron microscope (SEM) to find the presence of surface deformities and identify alterations on the surface in comparison to the base material.

Multi-Objective Optimization of EDM Parameters Using Grey Relational Analysis for Titanium Alloy (Ti–6Al–4V)

2014 ◽  
Vol 592-594 ◽  
pp. 540-544 ◽  
Author(s):  
A. Palanisamy ◽  
R. Rekha ◽  
S. Sivasankaran ◽  
C. Sathiya Narayanan
Keyword(s):  
Grey Relational Analysis ◽  
Removal Rate ◽  
Electrode Wear ◽  
Machining Parameters ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Edm Process

In this paper optimization of the electrical discharge machining (EDM) process with multiple performance characteristics based on the orthogonal array with the grey relational analysis was studied and investigated. A grey relational grade obtained from the grey relational analysis is used to solve the EDM process. Optimal machining parameters are determined by considering the grey relational grade as the performance index. The input independent parameters of peak current, pulse on time and pulse off time were examined and optimized on multiple response characters (material removal rate, electrode wear ratio and surface roughness). Experimental results have shown that machining performance in the EDM process can be improved effectively through this approach.

Multi-Objective Optimization of Surface Roughness and Electrode Wear in EDM Cylindrical Shaped Parts

2021 ◽  
Vol 1018 ◽  
pp. 59-64
Author(s):  
Le Hong Ky ◽  
Bui Thanh Danh ◽  
Nguyen Van Cuong ◽  
Nguyen Hong Linh ◽  
Tran Thi Hong ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Electrical Discharge Machining ◽  
Electrode Wear ◽  
Input Parameters ◽  
Grey Relational ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Calculated Model ◽  
Off Time ◽  
Optimum Input

The purpose of this work is to find an optimal combination of the input parameters when electrical discharge machining (EDM) cylindrical shaped parts so that both the surface roughness and the electrode wear are minimum. In this study, four input parameters including the pulse on time, the pulse off time, the current, and the serve voltage were taken into account. Experimental plan was designed based on L9 orthogonal array. Also, Taguchi method and Grey Relational Analysis (GRA) were joined for solving the multiobjective optimization problem and to find optimum input parameters. Experiments with optimal input parameters were performed for proving the predicted model. The experimental results of the surface roughness and the electrode wear matched with the calculated model. This indicates the proposed models can be used for practice.

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