Indexed In Scopus
  Scopus ID: 21100926589

Optimization of Process Parameters in Machining of AA-6262 by Implementing Grey Relational Analysis

Vinay Kumar Bandari, Venkateshwar Reddy Pathapalli, Naresh Kumar Sarella, Pranavi Uppu and Venkat Reddy Mitta

Abstract

In research employing computed numerical control (CNC) machining of AA-6262 and tungsten carbide tools, the impacts of three cutting parameters-the effects of three outcomes-material removal rate (MRR), surface roughness (SR), and tool wear rate (TWR)-of cutting speed, feed rate, and depth of cut (DoC)-were examined. In order to obtain as many responses as feasible, the study employed Taguchi’s design of Experiment approach and Grey relational analysis (GRA). The investigation’s findings showed that the answers were strongly impacted by the cutting settings. 2000 rpm, 400 rev/min for the feed rate, and 0.5 mm for the DoC were found to be the parameters’ ideal values. The validation test showed that the ideal settings produced the maximum rates of MRR, SR, and TWR. The work is important because it provides informative data on how the cutting settings impact how AA-6262 responds to CNC turning. The study’s conclusions may be used to improve turning performance and efficiency.

Published on: November 30, 2023
doi: 10.17756/nwj.2023-s4-066
Citation: Bandari VK, Pathapalli VR, Sarella NK, Uppu P, Mitta VR. 2023. Optimization of Process Parameters in Machining of AA-6262 by Implementing Grey Relational Analysis. NanoWorld J 9(S4): S389-S393.

Download Citation (XML)

10 Downloads
Bitnami