Experimental Analysis of CO2 Laser Cutting Characteristics for Aluminium 5052 Alloy Using Artificial Neural Network

Machining process efficiency can be improved by optimization the control parameters. This requires identifying and determining the value of critical process control parameters that lead to desired response ensuring a lower cost of manufacturing. A 〖CO〗_2 Laser can produce a coherent, convergent and monochromatic beam of electromagnetic radiation. Laser machining is thermal energy based non-contact type advance machining. The objective of the research work is to study the effect of 〖CO〗_2 Laser cutting parameters (Laser power, Gas pressure, Cutting speed, Laser pulse frequency, Nozzle tip distance) on the cut quality parameters (surface roughness, kerf width, Heat affected zone) at the problem associated with cutting of Aluminium5052 Alloy. The L_27 orthogonal array has been used for performing the experiments. An artificial neural network (ANN) method to optimize response parameters.