Optimization of Process Parameters Using a Genetic Algorithm for Process Automation in Aluminum Laser Welding with Filler Wire

용가 와이어를 적용한 알루미늄 레이저 용접에서 공정 자동화를 위한 유전 알고리즘을 이용한 공정변수 최적화

  • Park, Young-Whan (The BK21 Program for Research and Education in Mechanical Engineering, Hanyang University)
  • 박영환 (한양대학교 BK21 혁신설계 기계인력 양성사업단)
  • Published : 2006.10.31

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 kW 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 $N/mm^2$.

Keywords

References

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