scholarly journals Experimental Investigation of the Micro-hardness of EN-31 Die Steel in a Powder-Mixed Near-Dry Electric Discharge Machining Method

2020 ◽  
Vol 66 (3) ◽  
pp. 184-192 ◽  
Author(s):  
Sanjay Sundriyal ◽  
Vipin ◽  
Ravinderjit Singh Walia

The Powder-Mixed Near-Dry Electric Discharge Machining (PMND-EDM) methodology has proven to be efficient in terms of machining rate, surface morphology, and environmental friendliness, unlike traditional EDM. In this study, the presence of a conductive metallic powder (zinc) in the dielectric medium was responsible for changing the topography of the workpiece (EN-31) and resulted in a higher micro-hardness value of the machined component. In this research, an approach has been made to optimize the significant process parameters by using a Taguchi L9 orthogonal array (OA) to obtain machined components with higher values of micro-hardness, which was measured in terms of Vickers hardness HV. The selected process parameters were tool diameter, mist flow rate, metallic powder concentration, and dielectric mist pressure. By introducing foreign particles (metallic powder), the topography of the machined products has been improved, and the micro-hardness value was found to be enhanced. The confirmation experiment was performed for optimal process parameter settings, and the enhanced microhardness value was found to be 506.63 HV in the machined EN-31 die steel.

2020 ◽  
Vol 66 (4) ◽  
pp. 243-253 ◽  
Author(s):  
Sanjay Sundriyal ◽  
Vipin ◽  
Ravinderjit Singh Walia

Near-dry electrical discharge machining (ND-EDM) is an eco-friendly process. In this study, an approach has been made to make the machining process more efficient than ND-EDM with the addition of metallic powder with the dielectric medium to machine EN-31 die steel. Powdermixed near-dry EDM (PMND-EDM) has several advantages over the ND-EDM or conventional electrical discharge machining (EDM) process, such as a higher material removal rate (MRR), fine surface finish (Ra), sharp cutting edge, lesser recast layer, and lower deposition of debris. The output response variables are MRR, Ra, residual stress (RS) and micro-hardness (MH) of the machined surfaces. Further study of the workpiece was performed, and a comparative study was conducted between ND-EDM and PMND-EDM. In this proposed method of machining, the MRR, Ra, and MH increased by 17.85 %, 16.36 %, and 62.69 % while RS was reduced by 56.09 %.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
MD Sameer ◽  
Anil Kumar Birru ◽  
G. Srinu ◽  
Ch Naresh

Purpose The electric discharge machining (EDM) involves electrons discharged from the electrode and machining progresses due to the removal of the material from the component. This a thermal-based machining process primarily used for hard to machine components with conventional methods. This process is used to make intricate cavities and contours. The fabricated part is the replica of the tool material with high surface finish and good dimensional accuracy. This study aims to evaluate the comprehensive effect of process parameters on electric discharge machining of maraging steel. Design/methodology/approach Multiple criteria Decision making (MCDM) techniques are used to select the best parameters by comparing several responses to achieve the desired goal. There are different MCDM techniques available for optimization of machining parameters. In the current investigation, multi-objective optimization by data envelopment analysis based ranking (DEAR) approach was used for machining Maraging C300 grade steel. Findings The Taguchi L9 runs were planned with process parameters such as current (Amp), Tool diameter (mm) and Dielectric pressure (MPa). The effect of process parameters on the responses, namely, material removal rate (MRR), tool wear rate (TWR) and surface roughness (SR) were evaluated. High MRR is found at 15 A current, 14 mm tool diameter and dielectric pressure of 0.2 MPa. Optimum process parameters experiment showed reduced crack density. Originality/value An effort was made successfully to enhance the responses using the DEAR method and establish the decision making of selecting the optimal parameters by comparing the results obtained by machining maraging steel C300 grade.


2020 ◽  
Vol 27 ◽  
pp. 1051-1054
Author(s):  
M. Meignanamoorthy ◽  
M. Ravichandran ◽  
S. Sakthivelu ◽  
S. Dinesh Kumar ◽  
C. Chanakyan ◽  
...  

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