Combined Effect of Gas Tungsten Arc Welding Process Variants and Post-Weld Heat Treatment on Tensile Properties and Microstructural Characteristics of Ti–6Al–4V Alloy Joints

2020 ◽  
Vol 9 (2) ◽  
pp. 194-211 ◽  
Author(s):  
V. Vaithiyanathan ◽  
V. Balasubramanian ◽  
S. Malarvizhi ◽  
Vijay Petley ◽  
Shweta Verma
2012 ◽  
Vol 162 ◽  
pp. 531-536
Author(s):  
Gabriel Gorghiu ◽  
Paul Ciprian Patic ◽  
Dorin Cârstoiu

The paper presents a model of using the artificial neural networks when determining the relations of dependency between the observable parameters and the controllable ones in the case of RoboticGas Tungsten Arc Welding. The proposed model is based on the direct observation of welded joints, emphasizing on the process variables which have been arranged in the nodes of a neural network. The design of the network intended to achieve an architecture that contains four nodes in the input layer (all of them being controllable parameters) and two nodes in the output layer (one for each observable parameter).


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