Investigation towards surface roughness & material removal rate in Wire-EDM of aluminium alloy 6061 and 5083 using Taguchi method

Author(s):  
Mohd Saif ◽  
Satyam Tiwari
2021 ◽  
Vol 49 (3) ◽  
pp. 756-763
Author(s):  
Kapil Gupta

This work presents the wire-EDM of WC-Co composite and optimization of process parameters using an integrated technique of response surface methodology (RSM), Vise Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) and artificial bee colony (ABC) algorithm to obtain the best set of machinability indicators. Wire feed (WF), servo voltage (SV), pulse off-time (Pon) and pulse on-time (Poff) are the variable process parameters, whereas root mean square roughness (Rq), average surface roughness (Ra) and material removal rate (MRR) are the machinability indicators considered in the present work. A total of twenty nine experiments have been conducted based on Box Behnken design (BBD) technique of response surface methodology. VIKOR has been used for normalization of responses and followed by solving empirical models using ABC algorithm to obtain optimized process parameters setting. WF-12 m/min, SV-65V, Pon-116 µs, Poff-20 µs are the optimum wire-EDM parameters obtained by intelligent RSM-VIKOR-ABC technique that produced best values of Ra-4.51 µm, Rq-5.64 µm, MRR-0.061 mm3 /min simultaneously. The validation test confirmed an improvement up to 15% in the response characteristics which proved the effectiveness of this novel hybrid technique for optimization. The optimum parameter setting is for ready industrial reference to attain best surface quality and process productivity for WC-Co composite machining by wire-EDM.


2018 ◽  
Vol 28 ◽  
pp. 55-66 ◽  
Author(s):  
Kuldeep Singh ◽  
Khushdeep Goyal ◽  
Deepak Kumar Goyal

In research work variation of cutting performance with pulse on time, pulse off time, wire type, and peak current were experimentally investigated in wire electric discharge machining (WEDM) process. Soft brass wire and zinc coated diffused wire with 0.25 mm diameter and Die tool steel H-13 with 155 mm× 70 mm×14 mm dimensions were used as tool and work materials in the experiments. Surface roughness and material removal rate (MRR) were considered as performance output in this study. Taguchi method was used for designing the experiments and optimal combination of WEDM parameters for proper machining of Die tool steel (H-13) to achieve better surface finish and material removal rate. In addition the most significant cutting parameter is determined by using analysis of variance (ANOVA). Keywords Machining, Process Parameters, Material removal rate, Surface roughness, Taguchi method


Author(s):  
Wahaizad Safiei ◽  
Muhamad Ridzuan Radin Muhamad Amin

In this paper, the results of surface roughness (Ra) and material removal rate (MRR) are presented based on experimental studies of Electrical Discharge Machining (EDM) process parameters. Pulse ON time, pulse OFF time, peak current, gap voltage and jump speed are the selected input parameters and the experiments were conducted with Aluminium Alloy 5083 as a workpiece, copper as an electrode and the response variables are surface roughness (Ra) and material removal rate (MRR). Design of Experiment and Analysis of Variance (ANOVA) were applied to identify the optimum settings.The result shows that the significant factors for the value of surface roughness (Ra) and material removal rate (MRR) are pulses ON time and peak current.


Author(s):  
Gajanan Kamble ◽  
Dr. N. Lakshamanaswamy ◽  
Gangadhara H S ◽  
Sharon Markus ◽  
N. Rajath

Wire cut electrical discharge machining (WEDM) is a hybrid manufacturing technology which enables machining of all engineering materials. This research article deals with investigation on Optimization of the Process Parameters of the wire cut EDM of Bronze material of dimension (80*80*40) in mm. Material removal rate, Surface roughness and Kerf width were studied against the process parameters such as Pulse on time(TON), Pulse off time (TOFF) and Current(IP). The machining parameters for wire EDM were optimized for achieving the combined objectives. As there are three input parameters 27 experiments is carried out and full factorial is used. Optimized parameters were found using (ANOVA) and the error percentage can be validated and parameter contribution for the Material removal rate (MRR) and Surface roughness were found.


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