Computational modelling for laser profiling

In many modern technologies, miniaturization is an important trend and as such, micromachining has become the key in the fabrication of micro-parts in various industries. Advances in the laser technology combined with micromachining make it a more practical and attractive tool to support these various applications. The type of substrate surface and the microchannel geometry created is determined by the laser’s power /duty cycle and the scanning speed in microfluidic device manufacturing. The objective of this project is to develop an approximate quantitative model to predict and to classify the glass surface exposed to the laser for microchannel formation based on an evolutionary computation technique. As such, the time taken for laser parameter optimization for forming microchannel on the glass substrate can be greatly reduced. In addition, the microchannel’s depth and width is predicted through the thermal distribution modeling on the substrate. The first part of the project is to trace suitable coefficients to approximate the model through the use of Algorithm Development Environment for Problem Solving (ADEP) and DataFit software program. The models are derived based on acquired experimental data from a laser scanning process. The mathematic models used to profile the laser scanning process for microchannel fabrication were obtained. The second part of the project consists of the use of the finite element analysis software program, ANSYS to perform a thermal analysis on the soda-lime glass substrate to obtain the heat distribution area. The result could then be used to predict the channel’s depth and width.Bachelor of Engineerin