Master of Science in Industrial Engineering (MSIE)
Friction Stir Welding (FSW) is a solid state joining process that uses a non-consumable rotating welding tool to generate frictional heat at the welding location. Large forces are required to produce friction between the welding tool and the work piece which increases the wear rate of the welding tool in welding materials with high melting temperature. Several different approaches have been developed to address this problem. This thesis focuses on a new modification of friction stir welding, called Laser Assisted Friction Stir Welding, a process developed in the last decade. This process uses laser energy to preheat the work piece at a localized area ahead of the rotating tool, thus softening a volume of the work piece ahead of the tool. The work piece is then joined by the rotating tool as in conventional FSW. The amount of heat generated during welding determines the quality of the weld. Hence understanding the temperature distribution is necessary in determining the optimum process parameters for the welding process. In this thesis, a three dimensional model of laser assisted friction stir welding is developed, using FLUENT which is based on finite volume method, to obtain the temperature distribution in the work piece. The developed model can be used to better understand the process, predict the process performance and to determine optimal process parameters. A comparison with pure friction stir welding without laser assistance is also made to show its potential benefits. Parametric studies are designed to understand the effect of variation of certain process parameters such as feed rate, tool rotational speed and laser heat input on temperature distribution in the work piece. Finally, optimal combinations of friction stir welding and laser parameters are determined by a metaheuristic - Ant Colony Optimization.
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Daftardar, Shivani, "Laser assisted friction stir welding: finite volume method and metaheuristic optimization" (2009). LSU Master's Theses. 1748.
T. Warren Liao