TY - GEN
T1 - Optimization of Welding Dissimilar sheet metals using Taguchi and Grey based Taguchi Methods
AU - Devaraj, Jeyaganesh
AU - Ziout, Aiman
AU - Qudeiri, Jaber Abu
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - The scope of the present investigation is to find optimal input parameters of gas metal arc welding (GMAW) for joining two different sheets of steel. A butt joint is made from thin stainless steel SS304 and Mild steel AISI1008 of dimension 60mm×300mm×1.5mm. The L16 orthogonal array was used as the design of experiment (DOE) and a self-built CNC machine is used to fully automate the welding process. Single-objective optimization is performed using the Taguchi method and a multi-objective optimization model is developed by Grey based Taguchi method. The observations emphasize the significance of tensile strength and hardness of the welded joint. The joint characteristics are found to be improved by 7% using the optimized parameters. The percentage of contribution by input parameters is assessed using ANOVA. Wire feed rate and weld current are found to be the most influencing parameters. Furthermore, the microstructural analysis connotes the presence of courser martensite and ferrite in the heat affected zone making them vulnerable to fracture.
AB - The scope of the present investigation is to find optimal input parameters of gas metal arc welding (GMAW) for joining two different sheets of steel. A butt joint is made from thin stainless steel SS304 and Mild steel AISI1008 of dimension 60mm×300mm×1.5mm. The L16 orthogonal array was used as the design of experiment (DOE) and a self-built CNC machine is used to fully automate the welding process. Single-objective optimization is performed using the Taguchi method and a multi-objective optimization model is developed by Grey based Taguchi method. The observations emphasize the significance of tensile strength and hardness of the welded joint. The joint characteristics are found to be improved by 7% using the optimized parameters. The percentage of contribution by input parameters is assessed using ANOVA. Wire feed rate and weld current are found to be the most influencing parameters. Furthermore, the microstructural analysis connotes the presence of courser martensite and ferrite in the heat affected zone making them vulnerable to fracture.
KW - GMAW process
KW - Microstructural analysis
KW - Stainless steel
KW - Taguchi Optimization
KW - and Grey-based Taguchi method
UR - http://www.scopus.com/inward/record.url?scp=85128426031&partnerID=8YFLogxK
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U2 - 10.1109/ASET53988.2022.9734859
DO - 10.1109/ASET53988.2022.9734859
M3 - Conference contribution
AN - SCOPUS:85128426031
T3 - 2022 Advances in Science and Engineering Technology International Conferences, ASET 2022
BT - 2022 Advances in Science and Engineering Technology International Conferences, ASET 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2022 Advances in Science and Engineering Technology International Conferences, ASET 2022
Y2 - 21 February 2022 through 24 February 2022
ER -