Modelling tensile strength of friction stir welded aluminium alloy 1100 using fuzzy logic

Friction stir welding (FSW) is a promising technique in which joints with high strength and minimal defects can be realized by adopting optimum process parameters. The prominent parameters are tool rotation speed, welding speed, shoulder diameter and pin diameter of the tool. In this study Mamdani fuzzy system was used to generate the model for predicting and exploring the influence of FSW process parameters on tensile strength of AA1100 joints. The FSW trials are conducted at various levels of process parameters according to central composite design. The study proved that the process parameters had significant effect on the tensile strength of friction stir welded joints. Crest parabolic variation trend was observed in tensile strength of the joints, with respect to the interaction effects of TRS, WS and SD. Increase in pin diameter had positive effect in increasing the tensile strength of the joints, for any change in TRS, WS and SD. Maximum tensile strength of 72.4 MPa was obtained at tool rotation speed of 1050 rpm, welding speed of 60 mm/min, shoulder diameter of 18 mm and pin diameter of 6 mm. The methodology given in this paper delivers a useful tool to assess the tensile strength of friction stir welded AA1100.

[1]  R. Miranda,et al.  Influence of process parameters in the friction surfacing of AA 6082-T6 over AA 2024-T3 , 2013 .

[2]  V. Muthukumaran,et al.  Parameter Optimization for Friction Stir Welding AA1100 , 2015 .

[3]  V. Balasubramanian,et al.  Establishing relationships between mechanical properties of aluminium alloys and optimised friction stir welding process parameters , 2012 .

[4]  A. Khodabandeh,et al.  Correction to: Microstructure and mechanical properties of joints welded by friction-stir welding in aluminum alloy 7075-T6 plates for aerospace application , 2016 .

[5]  V. Balasubramanian,et al.  Multi-Response Optimization of Friction-Stir-Welded AA1100 Aluminum Alloy Joints , 2012, Journal of Materials Engineering and Performance.

[6]  H. Bhadeshia,et al.  Recent advances in friction-stir welding : Process, weldment structure and properties , 2008 .

[7]  S. Amini,et al.  Investigation of the effect of tool geometry on friction stir welding of 5083-O aluminum alloy , 2015 .

[8]  A. Khodabandeh,et al.  Microstructure and mechanical properties of joints welded by friction-stir welding in aluminum alloy 7075-T6 plates for aerospace application , 2016 .

[9]  Qiang Liu,et al.  Effect of tool pin eccentricity on microstructure and mechanical properties in friction stir welded 7075 aluminum alloy thick plate , 2014 .

[10]  R. Mishraa,et al.  Friction Stir Welding And Processing , 2005 .

[11]  K. Karthick,et al.  Process parameters effect on the strength of Friction Stir Spot Welded AA6061 , 2016 .

[12]  Anthony P. Reynolds,et al.  Effect of Tool Pin Thread Forms on Friction Stir Weldability of Different Aluminum Alloys , 2014 .

[13]  Ibrahim N. Tansel,et al.  Optimizations of friction stir welding of aluminum alloy by using genetically optimized neural network , 2010 .

[14]  V. Kishore,et al.  Numerical Simulation of Temperature Distribution and Material Flow During Friction Stir Welding of Dissimilar Aluminum Alloys , 2014 .

[15]  R. Padmanaban,et al.  Simulated Annealing Based Parameter Optimization for Friction Stir Welding of Dissimilar Aluminum Alloys , 2014 .

[16]  S. Babajanzade Roshan,et al.  Optimization of friction stir welding process of AA7075 aluminum alloy to achieve desirable mechanical properties using ANFIS models and simulated annealing algorithm , 2013, The International Journal of Advanced Manufacturing Technology.

[17]  L. Murr A Review of FSW Research on Dissimilar Metal and Alloy Systems , 2010 .

[18]  K. Mohandas,et al.  Comparative study of two soft computing techniques for the prediction of remaining useful life of cutting tools , 2015, J. Intell. Manuf..