Parameter optimization of micro ECDM process of borosilicate glass

Parameter optimization of micro ECDM process of borosilicate glass

Mohit VishnoiA.N. Veerendra Kumar S. Senthil Murugan 

Department of Mechanical Engineering, J S S Academy of Technical Education, Noida 201301, India

Department of Mechanical Engineering, Mepco Schlenk Engineering College, Sivakasi 626005, India

Corresponding Author Email: 
vishnoi.mohit06@gmail.com
Page: 
48-52
|
DOI: 
https://doi.org/10.18280/eesrj.050203
Received: 
April 25 2018
|
Accepted: 
June 3 2018
|
Published: 
30 June 2018
| Citation

OPEN ACCESS

Abstract: 

Electro Chemical Discharge Machining Process (ECDM) is a prominent hybrid machining process used in distinctness machining of hard and brittle non-conducting materials. ECDM has been exploited to fabricate micro-holes in non- conductive brittle materials. An experiment has been conducted on ECDM for micro drilling operation on borosilicate glass material according to the Taguchi Orthogonal Array (L9) technique in order to ascertain the effect of certain variables in the same manner with material removal rate (MRR) & tool wear rate (TWR). In superintending the machining performance, signal to noise ratio (S/N ratio) was calculated to find out the involvement in the main machining variables, such as applied voltage, electrolyte concentration and inter electrode gap. During the experiments, the non-conducting and highly brittle borosilicate glass material is used as a work-piece and NaOH as electrolyte solution. In addition to that, Graphite and Tungsten were used as cathode and anode respectively. In this research of Taguchi method was utilized to optimize the process variables which affect MRR and TWR. From main effect plot through Minitab software, it turns out that the inter-electrode gap has the supreme affect on MRR and TWR.

Keywords: 

electro chemical discharge machining (ECDM), material removal rate (MRR), tool wear rate (TWR), taguchi method

1. Introduction
2. Experimental Details
3. Measurement of Machining Performance
4. Process Parameter & Level Selection
5. Experimentation
6. Optimization of Process Parameters Using Taguchi Method
7. Results and Discussion
8. Conclusions
Nomenclature
  References

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