Optimization of Welding Process using a Genetic Algorithm

Author:

Élesztős Pavel1,Jančo Roland1,Voštiar Vladimír1

Affiliation:

1. Slovak University of Technology in Bratislava , Faculty of Mechanical Engineering, Institute of Applied Mechanics and Mechatronics , Nam. slobody 17, 812 31 Bratislava , Slovak Republic

Abstract

Abstract Welding is a complex technological process in which local heating takes place up to the melting point of the connecting and the additional material. Phase and crystallization processes are a strong non-linear function of the cooling rate. This non-linear function multiplies the complexity of the numerical simulation and optimization of the welding process. Lately, optimization with genetic algorithm has become the trend to optimize systems that behave in a non-linear manner and contain a number of local extremes. Genetic algorithm is therefore a method by which we seek an absolute extreme. It is a method which seeks a solution to near absolute extreme. In this paper the use of the genetic algorithm for welding process optimization is described.

Publisher

Walter de Gruyter GmbH

Subject

Mechanical Engineering

Reference11 articles.

1. [1] D.E. Goldberg. Genetic algorithm in Search, Optimization, and Machine Learning, Addison Wesley, Reading, MA 1989.

2. [2] L. Chambers. Practical Handbook of Genetic Algorithms, aplications, CRC Press, New York 2001.10.1201/9781420035568

3. [3] V. Kvasnička, J. Pospíchal, P. Tiňo. Evolutionary algorithms, STU, Bratislava 2000 (in Slovak).

4. [4] Sysweld: Reference manual, ESI Group, 2015.

5. [5] V. Voštiar. Numerical Analysis of Residual Streses after Welding in Planar Parts, Diploma Thesis, STU Engineering Faculty in Bratislava, Bratislava 2002 (in Slovak).

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