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Taguchi Based Optimization of Process Parameters for Friction Stir Welding of AA7075 and C11000


Santosh N. Bodake , Ashokrao Mane Group of Institutions, Vathar, Shivaji University, Kolhapur, India; Prof. Dr. A. J. Gujar, D. Y. Patil college of Engineering and Technology, Kolhapur, Shivaji University, Kolhapur, India


Friction Stir Welding (FSW), Aluminium Alloy


AA 7075 is an aluminium alloy, with zinc as the main alloying constituent. It has high strength, with similar to many steels, have good fatigue strength and average machinability, but has less resistance to corrosion than many other Al alloys. AA7075 are frequently used in transport applications such as marine, aviation and automotive due to their high strength to density ratio. Strength and light weight also desirable in fields such as Rock climbing equipment, bicycle components and airframes are commonly made from 7075 aluminium alloy. AA 7075 has low weldability due to reduced solidification microstructure, and when welded by fusion welding techniques go down its mechanical properties. Friction stir welding (FSW) is solid state, reliable joining techniques to retain the properties of the alloy as there is no melting of metal takes place, welding takes place due to the forging effect. As process parameter affects a lot on strength of joint so it is important to optimize process parameters. Process parameters for friction stir welding are tool pin profile, tool rotary speed, welding speed, and welding axial force, tool tilt angle and Tool shoulder. From above process parameters of FSW tool rotary speed, welding speed, and welding axial force effects most on mechanical strength. Current work deals with experimental investigation of optimization of friction stir welding process (FSW) to arrive at desirable mechanical properties of aluminum 7075 and C11000 plates. Responses recorded are Ultimate tensile strength, and hardness of weld zone. After conducting experimentation testing is done to measure ultimate tensile strength and micro Vickers hardness. Results are analysed in Minitab 16 for optimizing process parameters.

Other Details

Paper ID: IJSRDV6I40812
Published in: Volume : 6, Issue : 4
Publication Date: 01/07/2018
Page(s): 995-999

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