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Modelling of weld-bead geometry and hardness profile in laser welding of plain carbon steel using neural networks and genetic algorithms
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Singh, A., Cooper, David E., Blundell, N., Pratihar, D. K. and Gibbons, Gregory John (2014) Modelling of weld-bead geometry and hardness profile in laser welding of plain carbon steel using neural networks and genetic algorithms. International Journal of Computer Integrated Manufacturing , Volume 27 (Number 7). doi:10.1080/0951192X.2013.834469
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Official URL: http://www.dx.doi.org/10.1080/0951192X.2013.834469
Abstract
An attempt was made to predict weld-bead geometry and its cross-sectional micro-hardness profile produced by laser welding of plain carbon steel (DC05) for a given set of process parameters. Welding was done using ytterbium fibre laser by considering laser power, weld speed and distance of the focal point from the sample surface as the input parameters. Microscopy was used to measure the weld dimensions. Micro-indentation was made to measure the corresponding Vickers’ hardness along the horizontal cross section. Two different models were developed. The first model had mean hardness and weld-bead geometry represented by four geometrical dimensions of the weld (that is, top width, depth, mid-width and heat-affected-zone width at mid-depth) as the modelling outputs. The second model had the hardness profile plot interpolation parameters as the modelling outputs. Two different designs of neural networks were used for process-based modelling, namely counter-propagation neural network (CPNN) and feed-forward back-propagation neural network (BPNN), and their prediction capabilities were compared. For the feed-forward neural network, a genetic algorithm was later applied to enhance the prediction accuracy by altering its topology. Back-propagation was implemented using 12 different training algorithms. Mean generalisation error was used to compare the modelling accuracy of the neural networks.
| Item Type: | Journal Article | ||||||||
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| Subjects: | Q Science > QA Mathematics T Technology > TS Manufactures |
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| Divisions: | Faculty of Science > WMG (Formerly the Warwick Manufacturing Group) | ||||||||
| Library of Congress Subject Headings (LCSH): | Laser welding, Genetic algorithms, Neural networks (Computer science) , Computer integrated manufacturing systems | ||||||||
| Journal or Publication Title: | International Journal of Computer Integrated Manufacturing | ||||||||
| Publisher: | Taylor & Francis Ltd. | ||||||||
| ISSN: | 0951-192X | ||||||||
| Official Date: | 2014 | ||||||||
| Dates: |
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| Volume: | Volume 27 | ||||||||
| Number: | Number 7 | ||||||||
| DOI: | 10.1080/0951192X.2013.834469 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Restricted or Subscription Access | ||||||||
| Funder: | University of Warwick International Manufacturing Centre, Indian Institute of Technology Kharagpur |
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