This paper is published in Volume-4, Issue-4, 2018
Area
Non- Conventional Machining
Author
Love Kishore Sharma, Dilip Gehlot, Anil Kumar Sharma, Bhupendra Verma
Org/Univ
Jaipur Institute of Technology, Jaipur, Rajasthan, India
Pub. Date
17 July, 2018
Paper ID
V4I4-1227
Publisher
Keywords
Electrochemical Micro Machining (ECMM), Radial Over Cut (ROC), S1 Tool steel

Citationsacebook

IEEE
Love Kishore Sharma, Dilip Gehlot, Anil Kumar Sharma, Bhupendra Verma. RSM application for optimization of ECMM parameter using S1 Tool steel, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Love Kishore Sharma, Dilip Gehlot, Anil Kumar Sharma, Bhupendra Verma (2018). RSM application for optimization of ECMM parameter using S1 Tool steel. International Journal of Advance Research, Ideas and Innovations in Technology, 4(4) www.IJARIIT.com.

MLA
Love Kishore Sharma, Dilip Gehlot, Anil Kumar Sharma, Bhupendra Verma. "RSM application for optimization of ECMM parameter using S1 Tool steel." International Journal of Advance Research, Ideas and Innovations in Technology 4.4 (2018). www.IJARIIT.com.

Abstract

S1 tool steel (60WCrV7) are used for the production of cold shear knives, ejector pins, air hammers etc. It is very difficult to machine S1 Tool steel alloys using conventional machine tools due to high toughness, impact resistance, dimensional stability and high hardening capacity. The Electrochemical Machining (ECM), a non-traditional manufacturing process, is a prime choice for machining S1 Tool steel alloys. The main aim in present work is to investigate the influence of ECM process parameters, such as applied voltage (V), inter-electrode gap (IEG), electrolyte flow rate (F.R.) and electrolyte concentration (EC), on Radial Overcut (ROC) during machining S1 Tool steel material. An aqueous solution of sodium nitrate (NaNO3) is used as an electrolyte. The experimental strategy depends on design formulated using response surface methodology. The effects of process parameters as well as their interactions are investigated and the process parameters are optimized by application of the response surface methodology