Optimisation of process parameters in friction stir welding based on residual stress analysis: A feasibility study

Abstract The present paper considers the optimisation of process parameters in friction stir welding (FSW). More specifically, the choices of rotational speed and traverse welding speed have been investigated using genetic algorithms. The welding process is simulated in a transient, two-dimensional sequentially coupled thermomechanical model in ANSYS. This model is then used in an optimisation case where the two objectives are the minimisation of the peak residual stresses and the maximisation of the welding speed. The results indicate that the objectives for the considered case are conflicting, and this is presented as a Pareto optimal front. Moreover, a higher welding speed for a fixed rotational speed results, in general, in slightly higher stress levels in the tension zone, whereas a higher rotational speed for a fixed welding speed yields somewhat lower peak residual stress, however, a wider tension zone, leading to a substantially higher residual tensile force.

[1]  Michael A. Sutton,et al.  A Study of Residual Stresses and Microstructure in 2024-T3 Aluminum Friction Stir Butt Welds , 2002 .

[2]  M. N. James,et al.  Optimising FSW process parameters to minimise defects and maximise fatigue life in 5083-H321 aluminium alloy , 2008 .

[3]  M. Jahazi,et al.  Relationship between FSW parameters, hardness and tensile properties of 7075-T6 and 2098-T851 similar but welds , 2008 .

[4]  Aravind Srinivasan,et al.  Innovization: innovating design principles through optimization , 2006, GECCO.

[5]  T. W. Liao,et al.  Model based optimisation of friction stir welding processes , 2009 .

[6]  Radovan Kovacevic,et al.  Finite element modeling of friction stir welding—thermal and thermomechanical analysis , 2003 .

[7]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[8]  M. N. James,et al.  Residual stresses and fatigue performance , 2007 .

[9]  Anders A. Larsen,et al.  Optimization of friction stir welding using space mapping and manifold mapping—an initial study of thermal aspects , 2009 .

[10]  Yuh J. Chao,et al.  Effects of temperature-dependent material properties on welding simulation , 2002 .

[11]  Phil E. Irving,et al.  The role of residual stress and heat affected zone properties on fatigue crack propagation in friction stir welded 2024-T351 aluminium joints , 2003 .

[12]  H. Schmidt,et al.  Optimization of the Process Parameters for Controlling Residual Stress and Distortion in Friction Stir Welding , 2008 .

[13]  Cem Celal Tutum,et al.  Thermomechanical Modelling of Friction Stir Welding , 2009 .

[14]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[15]  M. Preuss,et al.  Microstructure, mechanical properties and residual stresses as a function of welding speed in aluminium AA5083 friction stir welds , 2003 .

[16]  Zhili Feng,et al.  Modelling of residual stresses and property distributions in friction stir welds of aluminium alloy 6061-T6 , 2007 .

[17]  Radovan Kovacevic,et al.  Thermal modeling of friction stir welding in a moving coordinate system and its validation , 2003 .

[18]  Xinhai Qi,et al.  Thermal and Thermo-Mechanical Modeling of Friction Stir Welding of Aluminum Alloy 6061-T6 , 1998 .

[19]  V. Balasubramanian,et al.  Process parameters optimization for friction stir welding of RDE-40 aluminium alloy using Taguchi technique , 2008 .

[20]  Jesper Henri Hattel,et al.  An analytical model for the heat generation in friction stir welding , 2004 .

[21]  Jesper Henri Hattel,et al.  Thermal modelling of friction stir welding , 2008 .

[22]  Thomas J. Lienert,et al.  Toward reliable calculations of heat and plastic flow during friction stir welding of Ti-6Al-4V alloy , 2008 .

[23]  Livan Fratini,et al.  Friction Stir Welding Lap Joint Resistance Optimization Through Gradient Techniques , 2007 .

[24]  Philip J. Withers,et al.  Dissimilar friction stir welds in AA5083-AA6082: The effect of process parameters on residual stress , 2006 .

[25]  P. Michaleris,et al.  Comparison of buckling distortion propensity for SAW, GMAW, and FSW , 2006 .

[26]  Philip J. Withers,et al.  Global mechanical tensioning for the management of residual stresses in welds , 2008 .

[27]  Martin P. Bendsøe,et al.  Estimation of the Welding Speed and Heat Input in Friction Stir Welding using Thermal Models and Optimization , 2007 .

[28]  A. Murphy,et al.  The Characterization of Friction Stir Welding Process Effects on Stiffened Panel Buckling Performance , 2006 .

[29]  Philip J. Withers,et al.  The effect of tensioning and sectioning on residual stresses in aluminium AA7749 friction stir welds , 2008 .

[30]  Jesper Henri Hattel,et al.  Modelling heat flow around tool probe in friction stir welding , 2005 .

[31]  K. Dang Van,et al.  Modelling of the residual state of friction stir welded plates , 2008 .

[32]  Kalyanmoy Deb,et al.  Unveiling innovative design principles by means of multiple conflicting objectives , 2003 .

[33]  Philip J. Withers,et al.  Simulation of the Effectiveness of Dynamic Cooling for Controlling Residual Stresses in Friction Stir Welds , 2008 .

[34]  Michael A. Sutton,et al.  Predicting residual thermal stresses in friction stir welded metals , 2006 .

[35]  Eckart Zitzler,et al.  Evolutionary algorithms for multiobjective optimization: methods and applications , 1999 .

[36]  Yuh J. Chao,et al.  Numerical simulation of transient temperature and residual stresses in friction stir welding of 304L stainless steel , 2004 .

[37]  Kalyanmoy Deb,et al.  Multi-objective Genetic Algorithms: Problem Difficulties and Construction of Test Problems , 1999, Evolutionary Computation.

[38]  R. K. Ursem Multi-objective Optimization using Evolutionary Algorithms , 2009 .