Explore AI based performance evaluation of underwater fiber laser transmission micro-channeling operation on PMMA material

Abstract

Extensive use of polymers has been found in the manufacturing and production of high-quality microfluidic devices with the advent of modern machining technologies. To use the appropriate material for specific purpose, selection of appropriate machining process becomes crucial. Present study deals with the investigation on the effect of process parameters of laser micro-channelling operation on polymethyl methacrylate (PMMA) plate of thickness 9 mm in partially submerged in water. A fiber laser, specifically one with a wavelength of 1064 nm, has been employed for machining due to its superior performance compared to Nd: YAG or CO2 lasers. Experiments are carried out to investigate the effect of various laser beam characteristics, such as pulse frequency (PF), laser power (LP), and scanning speed (SS), on the channel depth, kerf width, and heat affected zone width of the machined micro-channel. In this study, fuzzy-technique models for order preference by resemblance to the ideal solution (fuzzy-TOPSIS) have been developed. Additionally, multi-objective optimization of process parameters is performed using ratio analysis (MOORA). Both of the models namely fuzzy-TOPSIS and MOORA indicate that the optimal machining criteria for micro-channeling of PMMA are PF of 65 kHz, LP of 6.5 W and SS of 0.5 mm/s. An analysis of the surface morphological variations in correlation with the channel dimensions is also conducted utilizing scanning electron microscopy (SEM). The study emphasises the efficiency of the methodologies used as powerful tools for developing a comprehensive model and establishing the optimal LBM parameters.