A procedure for calibration and validation of FE modelling of laser-assisted metal to polymer direct joining. (1st January 2018) - Lambiase, F.; Genna, S.; Kant, R.
Graphical abstract: Highlights: Bonded area shown by laser assisted polymer to metal joints is studied. An integrated experimental-FE modelling approach was developed. An optimized calibration and validation procedure for the FE model is developed. Emissivity, coefficient absorption and transmittance were characterized. The developed FE model showed an accuracy of almost 87%. Abstract: The quality of the joints produced by means of Laser-Assisted Metal to Polymer direct joining (LAMP) is strongly influenced by the temperature field produced during the laser treatment. The main phenomena including the adhesion of the plastic to the metal sheet and the development of bubbles (on the plastic surface) depend on the temperature reached by the polymer at the interface. Such a temperature should be higher than the softening temperature, but lower than the degradation temperature of the polymer. However, the temperature distribution is difficult to be measured by experimental tests since the most polymers (which are transparent to the laser radiation) are often opaque to the infrared wavelength. Thus, infrared analysis involving pyrometers and infrared camera is not suitable for this purpose. On the other hand, thermocouples are difficult to be placed at the interface without influencing the temperature conditions. In this paper, an integrated approach involving both experimental measurements and a Finite Element (FE) model were used to perform such an analysis. LAMP of Polycarbonate and AISI304 stainless steel was performed by means of high power diode laser and the main process parameters i.e. laser power and scanning speed were varied. Comparing the experimental measurements and the FE model prediction of the thermal field, a good correspondence was achieved proving the suitability of the developed model and the proposed calibration procedure to be ready used for process design and optimization.