Open AccessOptimal weld bead profiles in the conduction mode LBW of thin Ti–6Al–4V alloy sheets
Author(s) -
Mooli Harish,
Srinivasa Rao Seeram,
Satyanarayana Goteti,
Nageswara Rao Boggarapu
Publication year - 2021
Publication title -
aims materials science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.367
H-Index - 16
eISSN - 2372-0484
pISSN - 2372-0468
DOI - 10.3934/matersci.2021042
Subject(s) - taguchi methods , materials science , welding , laser beam welding , spot welding , orthogonal array , mechanical engineering , metallurgy , composite material , engineering
Day by day laser welding (LW) is gaining industrial importance. Good quality of weld joints can be realized through this process. Because this process yields low distortion and small weld bead. Aerospace, nuclear, automotive, and biomedical industries are opting for the lightweight and corrosion resistance titanium alloys. This paper deals with the generation of optimal weld bead profiles in the conduction mode laser beam welding (LBW) of thin Ti–6Al–4V alloy sheets. Laser beam diameter, power and welding speed are the 3 LBW parameters, whereas, bead width, depth of penetration, heat affected zone and maximum temperature are the performance indicators (PIs). 3 levels are set for each LBW parameter. Taguchi's L 9 OA (orthogonal array) is selected to minimize the numerical simulations. ANSYS Fluent V16.0 with Vc++ code is used to develop a generic model. %Contribution of each process variable on the PIs is assessed performing ANOVA analysis. The range of PIs is assessed adopting the modified Taguchi approach. A set of optimal LBW parameters are identified considering a multi-objective optimization technique. For these optimal LBW parameters weld bead width is minimum, and the depth of penetration is maximum. Empirical relations for PIs are developed and validated with simulations. Utilizing the Taguchi's design of experiments, empirical relations are developed for the performance indicators in laser beam welding (LBW) simulations performing few trial runs and identified the optimal LBW process parameters.