Optimization of friction welding parameters using simulated annealing

Friction welding is a solid state bonding technique which utilizes the heat generated by rubbing of two faying surfaces for the coalescence of material. Friction welding process is normally considered as a multi-input and multi-output process. Optimization of friction welding parameters is required to get good quality joints. Present study establishes the relationship between the input variables and output variables. Heating pressure (HP), heating time (HT), upsetting time (UT) and upsetting pressure (UP) are the input variables. The flash features such as flash thickness (FT), flash height (FH) and flash width (FW) are considered as output variables. The relationship between these input and output variables is established through artificial neural network (ANN). ANN is suitably integrated with the optimization algorithm in order to minimize the metal loss without sacrificing the tensile strength of the joints. The variation between theoretical and experimental values of flash features is also analyzed.