Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA
To improve the corrosion resistant properties of carbon steel, usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long-...
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| Format: | Article |
| Language: | English |
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Wiley
2013-01-01
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| Series: | Journal of Engineering |
| Online Access: | http://dx.doi.org/10.1155/2013/285030 |
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| author | P. Sreeraj T. Kannan Subhashis Maji |
| author_facet | P. Sreeraj T. Kannan Subhashis Maji |
| author_sort | P. Sreeraj |
| collection | DOAJ |
| description | To improve the corrosion resistant properties of carbon steel, usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long-term reliability and performance. By cladding these properties can be achieved with minimum cost. The main problem faced on cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, and contact tip to work distance and pinch) to get optimum dilution in stainless steel cladding of low carbon structural steel plates using gas metal arc welding (GMAW). Experiments were conducted based on central composite rotatable design with full replication technique, and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. In this study, artificial neural network (ANN) and genetic algorithm (GA) techniques were integrated and labeled as integrated ANN-GA to estimate optimal process parameters in GMAW to get optimum dilution. |
| format | Article |
| id | doaj-art-04317a51d8304d4b94ece2ee9be9c7a4 |
| institution | OA Journals |
| issn | 2314-4904 2314-4912 |
| language | English |
| publishDate | 2013-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Engineering |
| spelling | doaj-art-04317a51d8304d4b94ece2ee9be9c7a42025-08-20T02:03:07ZengWileyJournal of Engineering2314-49042314-49122013-01-01201310.1155/2013/285030285030Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GAP. Sreeraj0T. Kannan1Subhashis Maji2Department of Mechanical Engineering, Valia Koonambaikulathamma College of Engineering and Technology, Trivandrum, Kerala 692574, IndiaSVS College of Engineering, Coimbatore, Tamilnadu 642109, IndiaDepartment of Mechanical Engineering, IGNOU, New Delhi 110068, IndiaTo improve the corrosion resistant properties of carbon steel, usually cladding process is used. It is a process of depositing a thick layer of corrosion resistant material over carbon steel plate. Most of the engineering applications require high strength and corrosion resistant materials for long-term reliability and performance. By cladding these properties can be achieved with minimum cost. The main problem faced on cladding is the selection of optimum combinations of process parameters for achieving quality clad and hence good clad bead geometry. This paper highlights an experimental study to optimize various input process parameters (welding current, welding speed, gun angle, and contact tip to work distance and pinch) to get optimum dilution in stainless steel cladding of low carbon structural steel plates using gas metal arc welding (GMAW). Experiments were conducted based on central composite rotatable design with full replication technique, and mathematical models were developed using multiple regression method. The developed models have been checked for adequacy and significance. In this study, artificial neural network (ANN) and genetic algorithm (GA) techniques were integrated and labeled as integrated ANN-GA to estimate optimal process parameters in GMAW to get optimum dilution.http://dx.doi.org/10.1155/2013/285030 |
| spellingShingle | P. Sreeraj T. Kannan Subhashis Maji Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA Journal of Engineering |
| title | Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA |
| title_full | Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA |
| title_fullStr | Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA |
| title_full_unstemmed | Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA |
| title_short | Estimation of Optimum Dilution in the GMAW Process Using Integrated ANN-GA |
| title_sort | estimation of optimum dilution in the gmaw process using integrated ann ga |
| url | http://dx.doi.org/10.1155/2013/285030 |
| work_keys_str_mv | AT psreeraj estimationofoptimumdilutioninthegmawprocessusingintegratedannga AT tkannan estimationofoptimumdilutioninthegmawprocessusingintegratedannga AT subhashismaji estimationofoptimumdilutioninthegmawprocessusingintegratedannga |