ANALYSIS OF THE HEAT AFFECTED ZONE IN CO2 LASER CUTTING OF STAINLESS STEEL

Abstract

This paper presents an investigation into the effect of the laser cutting arameters on the heat affected zone in CO2 laser cutting of AISI 304 stainless teel. The mathematical model for the heat affected zone was expressed as a unction of the laser cutting parameters such as the laser power, cutting speed, ssist gas pressure and focus position using the artificial neural network. To btain experimental database for the artificial neural network training, laser utting experiment was planned as per Taguchi's L27 orthogonal array with three evels for each of the cutting parameter. Using the 27 experimental data sets, the rtificial neural network was trained with gradient descent with momentum lgorithm and the average absolute percentage error was 2.33%. The testing ccuracy was then verified with 6 extra experimental data sets and the average redicting error was 6.46%. Statistically assessed as adequate, the artificial eural network model was then used to investigate the effect of the laser cutting arameters on the heat affected zone. To analyze the main and interaction effect f the laser cutting parameters on the heat affected zone, 2-D and 3-D plots were enerated. The analysis revealed that the cutting speed had maximum influence n the heat affected zone followed by the laser power, focus position and assist as pressure. Finally, using the Monte Carlo method the optimal laser cutting arameter values that minimize the heat affected zone were identified.

Keywords

Dates

  • Submission Date2012-04-24
  • Revision Date2012-07-04
  • Acceptance Date2012-07-12

DOI Reference

10.2298/TSCI120424175M

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