Volume : V, Issue : III, March - 2015
Prediction of process parameters of CO2Laser Cutting Machine for Aluminium 5052 Alloy Using ANN
Pankajbhai R. Prajapati, Vikram A. Patel
Abstract :
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 CO2 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 CO2 Laser cutting parameters (Laser power, Gas pressure, Cutting speed, Laser 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.
Keywords :
Laser Beam Machining (LBM) Quality parameters Artificial neural network method (ANN) Aluminium5052 Alloy GMDH shell regression
Article:
Download PDF
DOI : 10.36106/ijar
Cite This Article:
Pankajbhai R.Prajapati, Vikram A.Patel Prediction of Process Parameters of Co2 Laser Cutting Machine for Aluminium 5052 Alloy Using Ann Indian Journal of Applied Research, Vol.5, Issue : 3 March 2015
Number of Downloads : 657
Pankajbhai R.Prajapati, Vikram A.Patel Prediction of Process Parameters of Co2 Laser Cutting Machine for Aluminium 5052 Alloy Using Ann Indian Journal of Applied Research, Vol.5, Issue : 3 March 2015
Our Other Journals...
-
International Journal of
Scientific Research Visit Website -
PARIPEX Indian Journal
of Research Visit Website -
Global Journal for
Research Analysis Visit Website