Abstract
The diffusion of laser machines based on femtosecond and picosecond pulses is increasing in industry, thanks to their capacity of performing high precision, nano-scale machining operations, and to their applicability to a wide variety of materials. The quality of the obtained products depends heavily on the selection of proper machine parameters, which is a non-trivial task for such a nonlinear, multi-physics dependent process. In this work, we propose a new regression approach for the characterization of ablation threshold and incubation factor, which are the key parameters required for defining process recipes in ultra-short pulsed laser machining. The proposed method is applied to the estimation of these parameters for stainless steel AISI 316L, basing on hole drilling data measured by optical microscopy.
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