Open AccessExperimental Study on Laser Welding of AISI 304 Steel with Design of Experiments Approach
Author(s) -
Pawan Kumar Chellu,
R. Padmanaban,
R. Vaira Vignesh,
Abbhelash S Me,
S.M. Shariff,
G. Padmanabham
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/577/1/012117
Subject(s) - welding , materials science , butt joint , laser beam welding , austenitic stainless steel , joint (building) , response surface methodology , mechanical engineering , design of experiments , distortion (music) , process (computing) , penetration depth , metallurgy , structural engineering , corrosion , computer science , engineering , mathematics , optics , amplifier , statistics , physics , optoelectronics , cmos , machine learning , operating system
Austenitic stainless steels find extensive applications in engineering and structural parts requiring inherent corrosion resistance. The main objective of this study is to achieve good quality butt joint in 2.5-mm thick 304 grade Stainless Steel. The joint quality is quantified in terms of weld-bead dimensions. The main issue that manufacturers face is controlling the input process parameters, to get a good quality joint, with required weld bead geometry under controlled thermal distortion. The objective of this work is to select proper input process parameters that would result in desirable weld-bead profiles with minimal heat input. The critical process parameters influencing laser-welding were found using response surface methodology technique. The results proved that the developed model could efficiently predict the responses. The criteria demonstrated a possible reduction in top width of weld bead with enhanced depth of penetration, which automatically envisaged an increase in aspect ratio. A two-factor five-level criteria design was used for predicting the optimized parameters by performing multi-response optimization. Among them, the third criterion has shown a significant decrease in heat input and it was chosen as the best-optimized parameter.