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Estimation of laser hybrid welded joint strength by using genetic algorithm approach

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Title: Estimation of laser hybrid welded joint strength by using genetic algorithm approach
Authors: Canyurt, Olcay Ersel1 ocanyurt@pau.edu.tr, Kim, Hang Rae2 k55jajuppo@yonsei.ac.kr, Lee, Kang Yong2 KYL2813@yonsei.ac.kr
Source: Mechanics of Materials. Oct2008, Vol. 40 Issue 10, p825-831. 7p.
Subjects: Laser ablation, Industrial lasers, Strength of materials, Algorithms
Abstract: Abstract: The genetic algorithm approach is extended to the prediction of welding strength of the 6K21-T4 aluminum alloy materials. The welding strength of joint parts can be improved by selecting suitable welding parameters. It is affected by many parameters, such as wire type, shielding gas, laser energy, laser focus, traveling speed, wire feed rate. The model is based on dependence of the six welding parameters on the welded joint strength. The present paper describes the use of the stochastic search process based on genetic algorithms (GA), in estimating the strength value of the welded parts. Non-linear estimation models were developed using GAs. The genetic algorithm laser welding strength estimation model (GALWSEM) was developed to estimate the mechanical properties of the welded joint for alloy materials. The effects of six welding design parameters on the strength value using the GALWSEM have been examined. The good quality welded joints can be obtained by using the results produced by the GALWSEM. The results indicate that the better quality joint may be obtained by selecting the wire type of 5356, the laser focus of −1mm, the wire type of ER 4043 and the laser focus of 0mm. [Copyright &y& Elsevier]
Copyright of Mechanics of Materials is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 32842617
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  Data: Estimation of laser hybrid welded joint strength by using genetic algorithm approach
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  Data: <searchLink fieldCode="AR" term="%22Canyurt%2C+Olcay+Ersel%22">Canyurt, Olcay Ersel</searchLink><relatesTo>1</relatesTo><i> ocanyurt@pau.edu.tr</i><br /><searchLink fieldCode="AR" term="%22Kim%2C+Hang+Rae%22">Kim, Hang Rae</searchLink><relatesTo>2</relatesTo><i> k55jajuppo@yonsei.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Lee%2C+Kang+Yong%22">Lee, Kang Yong</searchLink><relatesTo>2</relatesTo><i> KYL2813@yonsei.ac.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22Mechanics+of+Materials%22">Mechanics of Materials</searchLink>. Oct2008, Vol. 40 Issue 10, p825-831. 7p.
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  Data: <searchLink fieldCode="DE" term="%22Laser+ablation%22">Laser ablation</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+lasers%22">Industrial lasers</searchLink><br /><searchLink fieldCode="DE" term="%22Strength+of+materials%22">Strength of materials</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Abstract: The genetic algorithm approach is extended to the prediction of welding strength of the 6K21-T4 aluminum alloy materials. The welding strength of joint parts can be improved by selecting suitable welding parameters. It is affected by many parameters, such as wire type, shielding gas, laser energy, laser focus, traveling speed, wire feed rate. The model is based on dependence of the six welding parameters on the welded joint strength. The present paper describes the use of the stochastic search process based on genetic algorithms (GA), in estimating the strength value of the welded parts. Non-linear estimation models were developed using GAs. The genetic algorithm laser welding strength estimation model (GALWSEM) was developed to estimate the mechanical properties of the welded joint for alloy materials. The effects of six welding design parameters on the strength value using the GALWSEM have been examined. The good quality welded joints can be obtained by using the results produced by the GALWSEM. The results indicate that the better quality joint may be obtained by selecting the wire type of 5356, the laser focus of −1mm, the wire type of ER 4043 and the laser focus of 0mm. [Copyright &y& Elsevier]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Mechanics of Materials is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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      – Type: doi
        Value: 10.1016/j.mechmat.2008.04.001
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      – Code: eng
        Text: English
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        PageCount: 7
        StartPage: 825
    Subjects:
      – SubjectFull: Laser ablation
        Type: general
      – SubjectFull: Industrial lasers
        Type: general
      – SubjectFull: Strength of materials
        Type: general
      – SubjectFull: Algorithms
        Type: general
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      – TitleFull: Estimation of laser hybrid welded joint strength by using genetic algorithm approach
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            NameFull: Canyurt, Olcay Ersel
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            NameFull: Kim, Hang Rae
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            NameFull: Lee, Kang Yong
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            – D: 01
              M: 10
              Text: Oct2008
              Type: published
              Y: 2008
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              Value: 01676636
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              Value: 40
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              Value: 10
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            – TitleFull: Mechanics of Materials
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