This paper is published in Volume-3, Issue-4, 2017
Area
Mechanical
Author
Jagjit Singh
Org/Univ
L. R Institute of Engineering & Technology, Solan, India
Pub. Date
29 July, 2017
Paper ID
V3I4-1258
Publisher
Keywords
Surface Roughness, MRR (Material Removal Rate), Orthogonal Array, Analysis of Variance (ANOVA), Grey-Taguchi Technique

Citationsacebook

IEEE
Jagjit Singh. Parametric Optimization of Hot Machining Process for Aisi4140 Material Using Grey Relational Technique., International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.

APA
Jagjit Singh (2017). Parametric Optimization of Hot Machining Process for Aisi4140 Material Using Grey Relational Technique.. International Journal of Advance Research, Ideas and Innovations in Technology, 3(4) www.IJARIIT.com.

MLA
Jagjit Singh. "Parametric Optimization of Hot Machining Process for Aisi4140 Material Using Grey Relational Technique.." International Journal of Advance Research, Ideas and Innovations in Technology 3.4 (2017). www.IJARIIT.com.

Abstract

In the industries, there is a need of materials with very high hardness and shear strength in order to satisfy industrial requirements. So many materials which satisfy the properties are manufactured. Machining of such materials with conventional method of machining was proved to be very costly as these materials greatly affect the tool life. So to decrease tool wear, power consumed and increase surface finish Hot Machining can be used. The L9 orthogonal array of a Taguchi experiment is selected for four parameters (speed, feed rate, depth of cut and temperature) with three levels (low, medium, and high) in optimizing the hot machining turning parameters on lathe.