Multi-objective Optimization of Process Parameters in Friction Stir Welding

Cem Celal Tutum, Jesper Henri Hattel

    Research output: Contribution to conferencePosterResearchpeer-review


    The objective of this paper is to investigate optimum process parameters in Friction Stir Welding (FSW) to minimize residual stresses in the work piece and maximize production efficiency meanwhile satisfying process specific constraints as well. More specifically, the choices of tool rotational speed and traverse welding speed have been sought in order to achieve the goals mentioned above using an evolutionary multi-objective optimization (MOO) algorithm, i.e. non-dominated sorting genetic algorithm (NSGA-II), integrated with a transient, 2- dimensional sequentially coupled thermo-mechanical model implemented in the FE-code, ANSYS. This thermo-mechanical model is then used in the aforementioned constrained MOO case where the two objectives are conflicting. Following this, two reasonable design solutions among those multiple trade-off solutions have been selected based on the cost and the quality preferences.
    Original languageEnglish
    Publication date2010
    Publication statusPublished - 2010
    Event2010 Genetic and Evolutionary Computation Conference - Portland, United States
    Duration: 7 Jul 201011 Jul 2010


    Conference2010 Genetic and Evolutionary Computation Conference
    Country/TerritoryUnited States
    Internet address


    • Multi-objective optimization
    • Evolutionary optimization
    • Simulation
    • Manufacturing


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