Multiple Performance Characteristics Optimization for AA8011 on Friction Stir Welding by RSM Based DEA

Article Preview

Abstract:

In this investigation, the optimization of the multiple responses of Vickers hardness, Impact strength with notched and Un-notched conditions of the process parameters of rotational speed, tool tilt angle and feed rate with the straight cam profiled tool is considered. The three factors, five level rotatable central composite design are selected to optimize the responses of friction stir welded AA 8011 aluminium alloys. The highest relative efficiency is found using the data envelopment analysis to predict the optimum parameters. It reveals that at the rotational speed of 680 RPM, the tool tilt angle of 85 degrees and the feed rate of 24 mm/min the good weld quality can be achieved.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

451-455

Citation:

Online since:

November 2015

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] R. K. Kesharwani, S. K. Panda, S. K. Pal, Multi objective optimization of friction stir welding parameters for Joining of Two Dissimilar Thin Aluminum Sheets, Procedia Materials Science, 6 (2014) 178 – 187.

DOI: 10.1016/j.mspro.2014.07.022

Google Scholar

[2] N.D. Ghetiya, K.M. Patel, Prediction of Tensile Strength in Friction Stir Welded Aluminium Alloy Using Artificial Neural Network, Procedia Technology 14 ( 2014 ) 274 – 281.

DOI: 10.1016/j.protcy.2014.08.036

Google Scholar

[3] A.K. Lakshminarayanan, C.S. Ramachandran, V. Balasubramanian, Feasibility of surface-coated friction stir welding tools to join AISI 304 grade austenitic stainless steel, Defence Technology 10 (2014) 360-370.

DOI: 10.1016/j.dt.2014.07.003

Google Scholar

[4] Zhihua Song, Kazuhiro Nakata, Aiping Wu, Jinsun Liao, Li Zhou, Influence of probe offset distance on interfacial microstructure and mechanical properties of friction stir butt welded joint of Ti6Al4V and A6061 dissimilar alloys, Materials and Design, 57 (2014).

DOI: 10.1016/j.matdes.2013.12.040

Google Scholar

[5] K. Palani, C. Elanchezhian and G.B. Bhasker, Multi Response DEA-Based Taguchi Optimization of Process Parameters on AA8011 Friction Stir Welded Aluminium Alloys, Applied Mechanics and Materials, 766-767 (2015) 921-927.

DOI: 10.4028/www.scientific.net/amm.766-767.921

Google Scholar

[6] Chih-Wei Tsai, Lee-Ing Tong, Chung-Ho Wang, Optimization of Multiple Responses Using Data Envelopment Analysis and Response Surface Methodology, Tamkang Journal of Science and Engineering, 13 (2010) 197-203.

Google Scholar

[7] C. Elanchezhian, B. Vijaya Ramnath, P. Venkatesan, S. Sathish,T. Vignesh, B. Vinay, K. Gopinath, Parameter Optimization of Friction Stir Welding Of AA8011-6062 Using Mathematical Method, Procedia Engineering 97 ( 2014 ) 775 – 782.

DOI: 10.1016/j.proeng.2014.12.308

Google Scholar

[8] V. Jaiganesh, B. Maruthu, E. Gopinath, Optimization of process parameters on friction stir welding of high density polypropylene plate, Procedia Engineering 97 ( 2014 ) 1957 – (1965).

DOI: 10.1016/j.proeng.2014.12.350

Google Scholar

[9] Huijie Zhang, Huijie Liu, Mathematical model and optimization for underwater friction stir welding of a heat-treatable aluminum alloy, Materials and Design 45 (2013) 206–211.

DOI: 10.1016/j.matdes.2012.09.022

Google Scholar

[10] G. Elatharasana V.S. Senthil Kumarb, An experimental analysis and optimization of process parameter on friction stir welding of AA 6061-T6 aluminum alloy using RSM, Procedia Engineering 64 ( 2013 ) 1227 – 1234.

DOI: 10.1016/j.proeng.2013.09.202

Google Scholar