JWJ > Volume 24(5); 2006 > Article
Journal of KWJS 2006 October;24(5) :67-73.
Published online January 4, 2007.
Optimization of Process Parameters Using a Genetic Algorithm for Process Automation in Aluminum Laser Welding with Filler Wire
YoungWhan Park
Correspondence:   Published online January 4, 2007
ABSTRACT
  Laser welding is suitable for welding to the aluminum alloy sheet. In order to apply the aluminum laser welding to production line, parameters should be optimized. In this study, the optimal welding condition was searched through the genetic algorithm in laser welding of AA5182 sheet with AA5356 filler wire. Second-order polynomial regression model to estimate the tensile strength model was developed using the laser power, welding speed and wire feed rate. Fitness function for showing the performance index was defined using the tensile strength, wire feed rate and welding speed which represent the weldability, product cost and productivity, respectively. The genetic algorithm searched the optimal welding condition that the wire feed rate was 2.7 m/min, the laser power was 4 ㎾ and the welding speed was 7.95 m/min. At this welding condition, fitness function value was 137.1 and the estimated tensile strength was 282.2 N/㎟.
Keywords: Automated laser welding;Aluminum laser welding;Process parameter optimization;Genetic algorithm;Regression model
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