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Bera, Tapas
- The History of Development of Gas Metal Arc Welding Process
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Authors
Affiliations
1 Department of Mechanical Engineering, Kalyani Government Engineering College, Kalyani – 741235, West Bengal, IN
1 Department of Mechanical Engineering, Kalyani Government Engineering College, Kalyani – 741235, West Bengal, IN
Source
Indian Science Cruiser, Vol 34, No 6 (2020), Pagination: 64-66Abstract
Gas metal arc welding (GMAW) process can be divided as a metal inert gas (MIG) welding and metal active gas (MAG) welding process. In the process, the electric arc is produced which is used to melt and fuse the given materials. Inert or active shielding gases are passed through the nozzle to protect the weld pool from atmospheric contamination. The development of MIG welding technique has been started in the 19th century when Humphry Davy acquired the electric arc in 1800. From the implementation of inert gas at that time to the use of carbon dioxide gas (CO2), the gas metal arc welding process went through a remarkable development, and that is why it is widely used nowadays in automobile, railway construction, ship buildings, power plant industry, etc. In this paper, the chronological developments of the gas metal arc welding process are discussed.Keywords
Welding, Arc Welding, GMAW, MAG, MIG, Gas Shielding, Robotic Welding.
References
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- Application of Artificial Neural Networks in Predicting Output Parameters of Gas Metal Arc Welding of Dissimilar Steels
Abstract Views :580 |
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Authors
Tapas Bera
1,
Santanu Das
1
Affiliations
1 Department of Mechanical Engineering, Kalyani Government Engineering College, Kalyani-741235, IN
1 Department of Mechanical Engineering, Kalyani Government Engineering College, Kalyani-741235, IN
Source
Indian Science Cruiser, Vol 35, No 3 (2021), Pagination: 26-30Abstract
Artificial Neural Network (ANN) can be used for prediction utilizing some learning method. Gas metal arc welding (GMAW) was reported in a previous work to join SS304L stainless steel and EN8 mild steel plates. The experimental data obtained are used for training the ANN to enable it predict the output. ANN model is constructed to estimate ultimate tensile strength, elongation and hardness of the weld joint. A data set is tested through the modeled ANN to have satisfactory results. Quite close estimation of the ANN predicted values can be made with the observed ultimate tensile strength, elongation and hardness of the weld joint.Keywords
GMAW, ANN, Dissimilar Welding, MIG, Modeling, MATLAB.References
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Abstract Views :164 |
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Authors
Affiliations
1 Department of Metallurgical and Materials Engineering, IIT Kharagpur - 721302,, IN
2 Department of Production Engineering, Jadavpur University, Kolkata - 700032,
3 Department of Mechanical Engineering, Kalyani Govt. Engineering College, Kalyani- 741235, West Bengal, IN
1 Department of Metallurgical and Materials Engineering, IIT Kharagpur - 721302,, IN
2 Department of Production Engineering, Jadavpur University, Kolkata - 700032,
3 Department of Mechanical Engineering, Kalyani Govt. Engineering College, Kalyani- 741235, West Bengal, IN
Source
Indian Science Cruiser, Vol 36, No 2 (2022), Pagination: 33-39Abstract
The analytical hierarchy process or AHP is a useful decision-making tool, and it is applied in this work in resistance spot welding where two different types of triple thin sheets consisting of aluminium, galvanized iron and stainless steel are joined. Combining both the AHP and ANN, a hybrid network is developed to eliminate the complexity of the experimental results to predict. The AHP-ANN hybrid network successfully predicted output parameters with less error. Correlation coefficient has been more than 0.98 and the applicability of this method..Keywords
ANN, AHP, Resistance Spot Welding, Welding, Dissimilar Welding, Hybrid NetworkReferences
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