In this paper, a laser surface micromachining process planning system is presented. In this system, based on a regression model approach, the empirical coefficients, which provide the material removal rate, are automatically generated by a specific software according to the different materials that have to be processed. Numerical models generally present some limits due to the elevated calculation time requested to simulate the laser micromachining of industrial features, especially when transient solutions are considered, and, for this reason, to carry out a useful industrial tool for the evaluation of the material removal rate, the regression model represents the best solution. The presented statistical method, avoiding physical considerations, correlates the material removal rate with the process parameters in a very short calculation time. The automatic procedure for the generation of the coefficients of the regression polynomial permits to easily extend the regression model to any working material and system configuration allowing us to determine the best process parameters in a very short period of time. The results of this work have been patented.

An automated procedure for material removal rate prediction in laser surface micromanufacturing

FORTUNATO, ALESSANDRO;TANI, GIOVANNI
2010

Abstract

In this paper, a laser surface micromachining process planning system is presented. In this system, based on a regression model approach, the empirical coefficients, which provide the material removal rate, are automatically generated by a specific software according to the different materials that have to be processed. Numerical models generally present some limits due to the elevated calculation time requested to simulate the laser micromachining of industrial features, especially when transient solutions are considered, and, for this reason, to carry out a useful industrial tool for the evaluation of the material removal rate, the regression model represents the best solution. The presented statistical method, avoiding physical considerations, correlates the material removal rate with the process parameters in a very short calculation time. The automatic procedure for the generation of the coefficients of the regression polynomial permits to easily extend the regression model to any working material and system configuration allowing us to determine the best process parameters in a very short period of time. The results of this work have been patented.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11585/94451
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