Impact resistance and hardness modelling of Aluminium alloy welds using square-headed friction-stir welding tool

5th National Conference on Processing and Characterization of Materials

Srinivas, J.^2 ; Sudhakar, U.^1 ; Srinivas, J.^2

Asst. Prof., Department of Mechanical Engineering, GMR IT-Rajam, India^1

Assoc. Prof., Department of Mech.Engg., NIT Rourkela, Rourkela

769 008, India^2

关键词: Material Flow;    Neural network model;    Optimized process;    Process Variables;    Rotational motion;    Tool rotations;    Vertical milling;    Weld performance;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/115/1/012002/pdf
DOI  :  10.1088/1757-899X/115/1/012002

来源: IOP

【 摘 要 】

This paper proposes modelling and optimization issues relating to friction-stir welding process of aluminium alloys. A specially prepared SS tool of square headed pin profile with cylindrical shoulder is used with a vertical milling machine. Effects of process variables including tool rotation and tool velocity on the weld performance are studied in terms of impact strength and hardness. Three different rotational motions and three welding speeds (feeds) of tool are considered at constant axial load (depth of cut) condition and altogether nine experiments are conducted on a vertical milling machine with specially prepared fixture. Each weld sample is then tested for its impact strength (IS) and hardness independently. A model is developed to correlate the relations between the hardness/impact strength with tool rotation and weld speed using neural networks. The optimized process conditions are predicted to improvise the impact strength and hardness of the weld. Further, the morphology of the weld is studied using SEM to know the material flow characteristics.