scholarly journals Effect of Porosity on the Fatigue Behavior of Gas Metal Arc Welding Lap Fillet Joint in GA 590 MPa Steel Sheets

Metals ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 241 ◽  
Author(s):  
Dong-Yoon Kim ◽  
Insung Hwang ◽  
Geunho Jeong ◽  
Munjin Kang ◽  
Dongcheol Kim ◽  
...  
Keyword(s):  
Arc Welding ◽  
Fatigue Behavior ◽  
Gas Metal Arc Welding ◽  
Steel Sheets ◽  
Metal Arc Welding ◽  
Fillet Joint

Microstructure and Bending Strength of Dissimilar SS400/SUS304 Steels T-Fillet Joint by Gas Metal Arc Welding

2018 ◽  
Vol 773 ◽  
pp. 189-195 ◽  
Author(s):  
Kittipong Kimapong ◽  
Surat Triwanapong
Keyword(s):  
Weld Metal ◽  
Base Metal ◽  
Arc Welding ◽  
Joint Strength ◽  
Gas Metal Arc Welding ◽  
Welding Current ◽  
High Chromium ◽  
Metal Arc Welding ◽  
Joint Properties ◽  
Fillet Joint

In this paper, experiments on welding a dissimilar SS400/SUS304 steel T-fillet joint using high chromium electrode, and an effect of welding current on joint properties were studied. T-joints wielded by the designed specific welding currents were mechanically prepared and systematically investigated for joint properties. The experimental results were summarized as follows. Dissimilar SS400/SUS304 steels T-fillet joint could be successfully welded using a gas metal arc welding process with no defect in a weld metal. The optimized welding current in this experiment was 160 A that showed the least crack length of 0.247 mm. from a bending test. A different chemical composition of low carbon steel and high chromium weld metal produced a small interface shown with a smaller mixed zone of reinforced elements and base metal. It was also affected to decrease in the joint strength. However, the increase in the welding current could increase a combination of reinforced elements and a base metal on the interface, and it showed an effect to increase in the joint strength.

scholarly journals Two gas metal arc welding process dataset of arc parameters and input parameters

Data in Brief ◽  
2021 ◽  
Vol 35 ◽  
pp. 106790
Author(s):  
Rogfel Thompson Martinez ◽  
Guillermo Alvarez Bestard ◽  
Sadek C. Absi Alfaro
Keyword(s):  
Arc Welding ◽  
Gas Metal Arc Welding ◽  
Welding Process ◽  
Metal Arc Welding ◽  
Input Parameters ◽  
Arc Welding Process

scholarly journals Out-of-Control Multivariate Patterns Recognition Using D2 and SVM: A Study Case for GMAW

Mathematics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 467
Author(s):  
Pamela Chiñas-Sanchez ◽  
Ismael Lopez-Juarez ◽  
Jose Antonio Vazquez-Lopez ◽  
Jose Luis Navarro-Gonzalez ◽  
Aidee Hernandez-Lopez
Keyword(s):  
Arc Welding ◽  
New Technologies ◽  
Gas Metal Arc Welding ◽  
Industrial Processes ◽  
Support Vector ◽  
Innovative Method ◽  
Metal Arc Welding ◽  
Vector Machines ◽  
Study Case ◽  
Multivariate Pattern

Industrial processes seek to improve their quality control, including new technologies and satisfying requirements for globalised markets. In this paper, we present an innovative method based on Multivariate Pattern Recognition (MVPR) and process monitoring in a real-world study case. By identifying a distinctive out-of-control multivariate pattern using the Support Vector Machines (SVM) and the Mahalanobis Distance D2 it is possible to infer the variables that disturbed the process; hence, possible faults can be predicted knowing the state of the process. The method is based on our previous work, and in this paper we present the method application for an automated process, namely, the robotic Gas Metal Arc Welding (GMAW). Results from the application indicate an overall accuracy up to 88.8%, which demonstrates the effectiveness of the method, which can also be used in other MVPR tasks.

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