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.

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.

scholarly journals Multi-Objective Optimization of Wire Electro Discharge Machining (WEDM) Process Parameters Using Grey-Fuzzy Approach

2018 ◽  
Vol 63 (1) ◽  
pp. 16-25 ◽  
Author(s):  
Partha Protim Das ◽  
Sunny Diyaley ◽  
Shankar Chakraborty ◽  
Ranjan Kumar Ghadai
Keyword(s):  
Process Parameters ◽  
Removal Rate ◽  
Machining Process ◽  
Wire Tension ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Fuzzy Logic Technique ◽  
Off Time

Wire electro discharge machining (WEDM) is a versatile non-traditional machining process that is extensively in use to machine the components having intricate profiles and shapes. In WEDM, it is very important to select the optimal process parameters so as to enhance the machine performance. This paper emphasizes the selection of optimal parametric combination of WEDM process while machining on EN31 steel, using grey-fuzzy logic technique. Process parameters such as servo voltage, wire tension, pulse-on-time and pulse-off-time were considered while taking into account several multi-responses such as material removal rate (MRR) and surface roughness (SR). It was found that pulse-on-time of 115 µs, pulse-off-time of 35 µs, servo voltage of 40 V and wire tension of 5 kgf results in a larger value of grey fuzzy reasoning grade (GFRG) which tends to maximize MRR and improve SR. Finally, analysis of variance (ANOVA) is applied to check the influence of each process parameters in the estimation of GFRG.

scholarly journals Taguchi Optimization In Machining Inconel 600 With WEDM Process Using Cryogenically Treated Brass Wire

2021 ◽  
Vol 309 ◽  
pp. 01110
Author(s):  
K. Satyanarayana ◽  
B Ramya Krishna ◽  
M. Bhargavi ◽  
R. Eswari Vasuki ◽  
K. Raj Kiran
Keyword(s):  
Surface Roughness ◽  
Metal Removal ◽  
Removal Rate ◽  
Machining Parameters ◽  
Inconel 600 ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process ◽  
Off Time ◽  
Brass Wire

Wire electric discharge machining (WEDM) is one amongst the unconventional machining processes which might cut all kinds of shapes with an accuracy of +/−0.001mm. It will cut the materials that conduct electricity and can even cut the exotic metals like tungsten carbide, Hastelloy, Inconel etc. In the present work, machining on Inconel 600 by wire EDM with cryogenically treated brass wire is performed. Brass wire of 0.25mm diameter has been cryogenically treated at −90°C, −100°C and −110°C temperatures separately. An Experimental layout is designed as per Taguchi’s L-9 orthogonal array and experiments were conducted by varying machining parameters viz. Voltage, Pulse ON time and Pulse OFF time. The machining parameters are optimized using Taguchi’s methodology for minimum surface roughness and maximum metal removal rate (MRR). A Mathematical regression model for surface roughness and MRR is generated with the help of regression analysis. Through the Analysis of Variance (ANOVA) It was found that for MRR, pulse on time is the foremost contributing factor with 32.69% and for surface roughness, pulse off time is the foremost contributing factor with 23.59%.

Multi-Objective Optimization of Electro Discharge Machining of NIMONIC 75 Using Taguchi-Based Gray Relational Analysis

2020 ◽  
pp. 1-16
Author(s):  
Maninder Singh ◽  
Shankar Singh
Keyword(s):  
Tool Material ◽  
Gray Relational Analysis ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Relational Analysis ◽  
Electro Discharge Machining ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Nimonic 75 ◽  
Off Time

New superalloys are potential materials in aircraft and power plant industries because of their properties like high-temperature strength, creep life and resistance to corrosion and oxidation at elevated temperatures. Because of the superior properties of superalloys, machining them using the conventional processes is a difficult task that is associated with high cost and poor accuracy. In this study, an attempt has been made to machine NIMONIC 75 superalloy by the electro discharge machining (EDM) process, using the Taguchi-based Gray Relational Analysis method for multi-objective optimization of material removal rate (MRR), tool electrode wear rate (TEWR) and surface finish (SF). The experiments conducted were based on [Formula: see text] (2[Formula: see text]) orthogonal array. Six input parameters namely tool material, peak current, gap voltage, pulse on-time, pulse off-time and tool lift time were considered in this study. The validation results proved that the parametric setting of tool material as copper, peak current as 12[Formula: see text]A, gap voltage as 50[Formula: see text]V, pulse on-time as 200[Formula: see text][Formula: see text]s, pulse off-time as 15[Formula: see text][Formula: see text]s and tool lift time as 2[Formula: see text]s, yields optimized values of the performance characteristics. SEM images indicate the presence of numerous surface irregularities, whereas the XRD test shows the formation of various carbides on the EDMed surface.

Performance Investigation of Powder Mixed Electro Discharge Machining of Hypoeutectic Al-Si Alloy Using Brass Electrode

2019 ◽  
Vol 6 (2) ◽  
pp. 31-43
Author(s):  
Baliram Rajaram Jadhav ◽  
M. S. Sohani ◽  
Shailesh Shirguppikar
Keyword(s):  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Input Parameter ◽  
Optimal Solution ◽  
Machining Parameters ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Pulse On Time ◽  
Taguchi’S Design Of Experiments ◽  
Grey Relation

The aim of this study is the multi- objective optimization of process parameters of Al- Si alloy in powder mixed electrical discharge machining for obtaining minimum surface roughness, minimum tool wear rate, and maximum material removal rate. The important machining parameters were selected as discharge current, voltage and pulse-on time. Experiments were conducted by selecting different operating levels for the three parameters according to Taguchi's Design of Experiments. The multi-objective optimization was performed using Grey Relation Analysis to determine the optimal solution. The Grey Relation Grade values were then analysed using analysis of variance to determine the most contributing input parameter. On analysis it was found that peak current, pulse-on time, and voltage had an influence of 94.73%, 3.32% and 0.36%, respectively, on the multi-performance characteristics.

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 Metaheuristic Approach of Multi-Objective Optimization during EDM Process

2018 ◽  
Vol 3 (3) ◽  
pp. 301-314 ◽  
Author(s):  
Goutam Kumar Bose ◽  
Pritam Pain
Keyword(s):  
Regression Analysis ◽  
Removal Rate ◽  
Test Results ◽  
Multi Objective Optimization ◽  
Machining Processes ◽  
Multi Objective ◽  
Contour Plots ◽  
The Individual ◽  
Pulse On Time ◽  
Edm Process

In modern-day manufacturing Electric Discharge Machining (EDM) process has successfully placed itself in the domain of precision machining and generating complex geometries where secondary machining processes are eliminated. In this research paper, a die sinking EDM is applied to machine mild steel in order to measure the different multi-objective results like Material Removal Rate (MRR) and Over Cut (OC). This contradictory objective is accomplished by using the control parameters like a pulse on time, duty factor, gap current and spark gap employing copper tool with lateral flushing. Here the individual objective function of the responses is created through regression analysis. Primarily the contradictory objectives are optimized by employing Taguchi Methodology, then Regression analysis is done on the test results. Additionally, the experimental results are optimized using Response Surface Methodology (RSM). It is followed by a multi-objective optimization through Overlaid contour plots and Desirability functions to ascertain the best parametric combination amongst the set of feasible alternatives.

Performance Analysis on Eco-friendly Machining of Ti6Al4V using Powder Mixed with Different Dielectrics in WEDM

2020 ◽  
Vol 17 (3) ◽  
pp. 8128-8139
Author(s):  
S. Chakraborty ◽  
S. Mitra ◽  
D. Bose
Keyword(s):  
Metal Removal ◽  
Removal Rate ◽  
Machining Process ◽  
Process Efficiency ◽  
Machining Parameters ◽  
Dielectric Fluids ◽  
High Emission ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Wedm Process

The recent scenario of modern manufacturing is tremendously improved in the sense of precision machining and abstaining from environmental pollution and hazard issues. In the present work, Ti6Al4V is machined through wire EDM (WEDM) process with powder mixed dielectric and analyzed the influence of input parameters and inherent hazard issues. WEDM has different parameters such as peak current, pulse on time, pulse off time, gap voltage, wire speed, wire tension and so on, as well as dielectrics with powder mixed. These are playing an essential role in WEDM performances to improve the process efficiency by developing the surface texture, microhardness, and metal removal rate. Even though the parameter’s influencing, the study of environmental effect in the WEDM process is very essential during the machining process due to the high emission of toxic vapour by the high discharge energy. In the present study, three different dielectric fluids were used, including deionised water, kerosene, and surfactant added deionised water and analysed the data by taking one factor at a time (OFAT) approach. From this study, it is established that dielectric types and powder significantly improve performances with proper set of machining parameters and find out the risk factor associated with the PMWEDM process.

Mathematical Modeling of Machining Parameters in Electrical Discharge Machining with Cu-B4C Composite Electrode

2012 ◽  
Vol 488-489 ◽  
pp. 871-875
Author(s):  
V. Anandakrishnan ◽  
V. Senthilkumar
Keyword(s):  
Mathematical Models ◽  
Current Pulse ◽  
Electrical Discharge ◽  
Electrical Discharge Machining ◽  
Removal Rate ◽  
Machining Parameters ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time ◽  
Selection Of

Copper based metal matrix composite reinforced with Boron Carbide is a newly developed Electrical Discharge Machining (EDM) electrode showing better performance than the conventional copper based electrode. Right selection of machining parameters such as current, pulse on time and pulse off time is one of the most important aspects in EDM. In this paper an attempt has been made to develop mathematical models for relating the Material Removal Rate (MRR), Tool Removal Rate (TRR) and Surface roughness (Ra) to machining parameters (current, pulse-on time and pulse-off time). Furthermore, a study was carried out to analyze thSubscript texte effects of machining parameters on various performance parameters such as, MRR, TRR and Ra. The results of Analysis of Variance (ANOVA) indicate that the proposed mathematical models, can adequately describe the performance within the limits of the factors being studied. Response surface modeling is used to develop surface and contour graphs to analyze the effects of EDM input parameters on outer parameters.

scholarly journals Multi- Response Optimization of Wire EDM Process Parameter on Aluminium Alloy (5086)

2020 ◽  
Vol 10 (1) ◽  
pp. 224-229
Keyword(s):  
Aluminium Alloy ◽  
Material Removal Rate ◽  
Material Removal ◽  
Control Parameter ◽  
Removal Rate ◽  
Response Optimization ◽  
High Pulse ◽  
Pulse On Time ◽  
Pulse Off Time ◽  
Off Time

In the present work, the effect of process parameters on material removal rate during the machining of aluminium alloy (5086) with WEDM is studied. The four control parameter were selected i.e pulse on time (TON), pulse off time (TOFF), peak current (IP), and spark gap voltage (SV) to investigate their effects on material removal rate (MRR). Each control parameter had three levels. Total 27 experiments were done with a zinc coated brass wire of diameter 0.25 mm. Taguchi L9 orthogonal array technique was used for the experiment. ANOVA was used to find out the significance of control parameters and their contribution on MRR. It was found that maximum material removal rate was 41.52 mm3 /min which was due to high pulse on time and low pulse off time.

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