EXPERIMENTAL INVESTIGATION AND COMPARATIVE STUDY OF CNC MILLING PROCESS PARAMETER BY FACTORIAL METHODS WITH TAGUCHI METHOD ON ALUMINUM ALLOY

K Nagamani; B Venkatesh; N Keerthi

doi:10.29121/shodhkosh.v4.i2.2023.2650

Authors

K Nagamani Assistant Professor Department of Mechanical Engineering, Annamacharya University, Rajampet
Dr. B Venkatesh Assistant Professor Department of Mechanical Engineering, Annamacharya University, Rajampet
N Keerthi Assistant Professor Department of Mechanical Engineering, Annamacharya University, Rajampet

DOI:

https://doi.org/10.29121/shodhkosh.v4.i2.2023.2650

Keywords:

CNC Milling, One Factor at a Time (OFAT), Taguchi Method, Aluminum Alloy 6061, Material Removal Rate (MRR), Surface Roughness (Ra), Temperature, Process Optimization

Abstract [English]

This study explores the comparative effectiveness of the One Factor at a Time (OFAT) and Taguchi methods in optimizing CNC milling parameters for aluminum alloy 6061. The primary aim is to enhance the material removal rate (MRR) and minimize surface roughness (Ra) and temperature under both coolant and non-coolant conditions. A systematic approach is employed, involving a series of CNC milling experiments where depth of cut, feed rate, and spindle speed are varied. By utilizing both one factor at a time and Taguchi methods, this research seeks to identify the most influential factors affecting MRR, Ra, and temperature. The Taguchi method is applied for its robust design capabilities, while the one factor at a time method isolates individual parameters to assess their impact. The Percentage of Variation in Ra and temperature, with and without coolant, is analyzed for both methods to determine their efficacy in process optimization. Through nine experimental trials, the study aims to ascertain which method provides superior results in terms of optimizing MRR and reducing Ra and temperature. The findings will offer significant insights into the effectiveness of each method, contributing to the improvement of CNC milling processes. This research not only advances the understanding of process optimization in CNC machining but also provides practical recommendations for selecting the most suitable optimization approach based on specific machining objectives.

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