Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/2410
Title: Experimental Investigations and Analysis of Friction Stir Welding of Aluminium
Authors: Makvana, Sanjay
Keywords: Friction Stir Welding
Aluminium Alloy
Design of Experiments
Tensile Strength
Mechanical 2009
Project Report 2009
Mechanical Project Report
Project Report
09MME
09MME007
CAD/CAM
CAD/CAM 2009
Issue Date: 1-Jun-2011
Publisher: Institute of Technology
Series/Report no.: 09MME007
Abstract: Aluminium alloy has gathered wide acceptance in the fabrication of light weight structures requiring a high strength to weight ratio. Compared to the fusion welding processes that are routinely used for joining aluminium alloys, Friction Stir Welding (FSW) process is an emerging solid state joining process in which the material that is being welded does not melt and recast. Friction Stir Welding is the most remarkable welding technology that has been invented and developed in last two decades. This process uses a non-consumable tool to generate frictional heat in the abutting surfaces. The welding parameters such as tool shoulder diameter, tool rotational speed, weld- ing speed, axial force play a major role in deciding the joint strength. In present study an attempt has been made to develop a mathematical model to predict tensile strength of the friction stir welded AA8011 aluminium alloy by incorporating FSW process parameters. Four factors, ve levels central composite design has been used to minimize number of experimental conditions. Response surface method (RSM) has been used to develop the model. Adequacy of developed model has been checked by statistical tool analysis of variance (ANOVA) and validated by Chi square test. Since the response surface equation has been de- rived from quadratic regression t, conformation experiments have been performed to verify validity of model. The developed mathematical model can be e ectively used to predict the tensile strength of FSW joints. Further the tensile strength model has been optimized using genetic algorithm (GA) which gives maximum values of tensile strength and their respective optimal conditions.
URI: http://hdl.handle.net/123456789/2410
Appears in Collections:Dissertation, ME (CAD/CAM)

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