This study has been performed to evaluate basic characteristics of CW-CO$_2$ laser welding process of A5083 and A7N01 Al alloy. The effect of welding parameters, such as shielding gas, gas flow rate, laser power and welding speed on the bead shape and porosity from bead on plate welding tests have been investigated. Welds shielded by He gas had deeper penetration and better bead shape than those shielded by Ar. The penetration depth was augmented with the increase of laser Power and the decrease of welding speed. Welds of A7N01 alloy had deeper penetration than those of A5083 alloy In beads of A5083 alloy which has deeper penetration, the volume fraction of porosities was high due to the number of its was few, but size of its was larger. The case of deeper penetration beads of A7N01 alloy, the porosity reduced under relatively higher power The Volume fraction of porosities in weld of A5083 alloy was significantly higher than that in weld of A7N01 alloy.

When a high-power laser beam is irradiated on the surface of material, it is well known that a cavity, called a keyhole induced by the pressure action of the vapor plume, is generated in the molten material. This paper describes the interaction between a pulsed CO$_2$ laser beam and water. The laser-beam is used to generate and maintain a conical depression in the water surface similar to the keyhole created during laser penetration welding. Experimental results show that the depth of laser-beam penetration is limited by hydrodynamic instability. The instability of the surface cavity can be understood by the capillary instability of a hollow jet. Theoretical computation of the steady keyhole shape has been performed. modifying the model suggested by Andrews et al. (1976). The model predicts the qualitative behavior of the keyhole but significantly underestimates the average diameter.

The laser strengthening of 35kgf/㎟ and 60kgf/㎟ grade steel sheets is investigated by using CO$_2$ laser beam irradiation. The increase of tensile strength is dominated by the number of fully penetrated melting line. Also. the optimal laser input energy(hardness) and the number of melting line (melting width) are important variables for laser strengthening. Local strengthening by laser beam may be effective for the weight reduction of components where the tailored welded blank can not be applied.

A development of in-process and reliable monitoring system in laser materials processing is essential for successful applications toward the real industrial fields. It was known that optical signals induced by laser-matter interactions provide a good indication not only to monitor various defects but also to characterize and identify the process However there are still difficulties to implement the optical monitoring system in real fields since the system is susceptible to the spurious change of the signal affected by the variation of experimental conditions and environmental noises. In this article. a new type of optical monitoring technique named 'chromatic modulation technique' is described as a reliable, robust and sensitive monitor for the applications in laser materials processing in order to tackle the conventional problems in optical system.

This paper introduces a cleaning process for removing submicron-sized particles from NiP hard disk substrates by the liquid-assisted laser cleaning technique. Measurements of cleaning Performance and time-resolved optical diagnostics are Performed to analyze the physical mechanism of contaminant removal. The results reveal that nanosecond laser pulses are effective for removing the contaminants regardless of the wavelength and that a thermal mechanism involving explosive vaporization of liquid dominates the cleaning process.

This study deals with the laser cutting of stencil for the PCB. The most important aim of this study is to determine optimal conditions which make good-qualify stencil in Nd:YAG laser cutting. We made an experiment according to various variables (power. type of mask. gas pressure, cutting speed, and pulse width) and analyzed the cutting characteristics (surface roughness, kerf width. dross) . Each variable has optimal value for good-qualify cut edge under fixed condition. And neural network after learning experimental data with a million time iteration could predict surface roughness of cut edge under arbitrary condition approximately.