Multi-Response Optimization in Turning of AA6061 T6 Using Desirability Function Analysis

P. Jayaraman; L. Mahesh Kumar

doi:10.4028/www.scientific.net/AMM.812.124

Paper Titles

Optimal Blend for the Performance and Emission Analysis of C.I & V.C.R Engine Fuelled with Animal Tallow Methyl Esters (ATME) Blended with Diesels
p.79

Optimization of Operating Parameters on Wear Behavior of Manganese Phosphate Coated Die Steel
p.87

Optimal Current Value Estimation for an Automotive Magneto Rheological (MR) Fluid Damper Actuation
p.93

A Review on the Performance of Tribological Properties of Cutting Fluids
p.102

Enhancement of Wear Properties on High Speed Steel Tool Using PVD Coating Technique
p.107

Effective Fuel Consumption by Improving Cooling Water Flow Rate in IC Engine
p.112

Discussions about the Thermodynamic Entropy Property and its Existence in Vehicle Dynamics of Automobiles for Improving the Mileage
p.118

Multi-Response Optimization in Turning of AA6061 T6 Using Desirability Function Analysis
p.124

Heat Transfer Analysis of Extruded Rectangular Fin over Conventional Rectangular Fins by Numerical Simulation
p.130

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 812Multi-Response Optimization in Turning of AA6061...

Multi-Response Optimization in Turning of AA6061 T6 Using Desirability Function Analysis

Abstract:

This paper presents an ideal approach for the optimization of machining parameters on turning of AA6061 T6 aluminium alloy with multiple responses based on orthogonal array with desirability function analysis. In this study, turning parameters namely cutting speed, feed rate and depth of cut are optimized with the considerations of multiple responses such as surface roughness (R_a), roundness (Ø) and material removal rate (MRR). Multi response optimization of machining parameters was done through desirability function analysis. The optimum machining parameters have been identified by a composite desirability value obtained from desirability function analysis. The performance index and significant contribution of process parameters were determined by analysis of variance.

You might also be interested in these eBooks

Evolution of Green Energy and Vehicle Technology

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 812)

Pages:

124-129

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.812.124

Citation:

Cite this paper

Online since:

November 2015

Authors:

P. Jayaraman*, L. Mahesh Kumar

Keywords:

ANOVA, Desirability Function Analysis, Optimization, Orthogonal Array, Turning

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Aman Aggarwal, Hari Singh, Pradeep Kumar, Manmohan Singh, Optimization of multiple quality characteristics for CNC turning under cryogenic cutting environment using desirability function, Journal of Material Processing Technology, 205 (2008).

DOI: 10.1016/j.jmatprotec.2007.11.105

Google Scholar

[2] Shiv Sharma, Santosh Tamang, D. Devarasiddappa, M. Chandrasekran, Fuzzy logic modeling and multiple performance optimization in turning GFRP composites using desirability function analysis, Procedia Material science, 6 (2014) 1805-1814.

DOI: 10.1016/j.mspro.2014.07.211

Google Scholar

[3] Sharad Kumar Pradhan, Surendra Kumar Saini, Multi-Objective Optimization of CNC Turning Machining Parameters, Advanced Materials Research, 1016 (2014) 172 -176.

DOI: 10.4028/www.scientific.net/amr.1016.172

Google Scholar

[4] Santosh Tamang1, M. Chandrasekaran, Desirability fuzzy approach for optimizing multiple performance characteristics in machining metal matrix composites, Applied Mechanics and Materials, 592-594 (2014) 128-133.

DOI: 10.4028/www.scientific.net/amm.592-594.128

Google Scholar

[5] T. S. Mahesh Babu, P. S. Ramkumar, N. Muthukrishnan, Optimization of Machining Parameters on Turning of Hybrid Metal Matrix Composite, Applied Mechanics and Materials, 315 (2013) 113-116.

DOI: 10.4028/www.scientific.net/amm.315.113

Google Scholar

[6] Chorng-Jyh Tzeng, Yu-Hsin Lin, Yung-Kuang Yang, Ming-Chang Jeng, Optimization of turning operations with multiple performance characteristics using the Taguchi method and Grey relational analysis, Journal of Materials Processing Technology, 209 (2009).

DOI: 10.1016/j.jmatprotec.2008.06.046

Google Scholar

[7] P. Jayaraman, L. Mahesh kumar, Multi-response Optimization of Machining Parameters of Turning AA6063 T6 Aluminium Alloy using Grey Relational Analysis in Taguchi Method, Procedia Engg., 97 (2014) 197-204.

DOI: 10.1016/j.proeng.2014.12.242

Google Scholar

[8] Surendra Kumar Saini, Sharad Kumar Pradhan, Optimization of Multi-Objective Response during CNC Turning using Taguchi-Fuzzy Application, Procedia Engineering, Vol. 97, pp.141-149, (2014).

DOI: 10.1016/j.proeng.2014.12.235

Google Scholar