Abstract: Laser beam welding for the dissimilar Titanium and
Aluminium thin sheets is an emerging area which is having wider
applications in aerospace, aircraft, automotive, electronics and in
other industries due to its high speed, non-contact, precision with low
heat effects, least welding distortion, low labor costs and convenient
operation. Laser beam welding of dissimilar metal combinations are
increasingly demanded due to high energy densities with small fusion
and heat affected zones. Furthermore, no filler or electrode material is
required and contamination of weld is also very small. The present
study is to reviews the influence of different parameters like laser
power, welding speed, power density, beam diameter, focusing
distance and type of shielding gas on the mechanical properties of
dissimilar metal combinations like SS/Al, Cu/Al and Ti/Al focusing
on aluminum to other materials. Research findings reveal that Ti/Al
combination gives better metallurgical and mechanical properties
than other combinations such as SS/Al and Cu/Al.
Abstract: Laser beam welding has wide acceptability due to least welding distortion, low labour costs and convenient operation. However, laser welding for dissimilar titanium and aluminium alloys is a new area which is having wider applications in aerospace, aircraft, automotive, electronics and other industries. The present study is concerned with welding parameters namely laser power, welding speed, focusing distance and type of shielding gas and thereby evaluate welding performance of titanium and aluminium alloy thin sheets. This paper reviews the basic concepts associated with different parameters of Ti/Al sheet joint using Laser beam welding.
Abstract: Today automobile and aerospace industries realise Laser Beam Welding for a clean and non contact source of heating and fusion for joining of sheets. The welding performance is mainly based on by the laser welding parameters. Some concepts related to Artificial Neural Networks and how can be applied to model weld bead geometry and mechanical properties in terms of equipment parameters are reported in order to evaluate the accuracy and compare it with traditional modeling schemes. This review reveals the output features of Titanium and Aluminium weld bead geometry and mechanical properties such as ultimate tensile strength, yield strength, elongation and reduction of the area of the weld using Artificial Neural Network.