STUDIES IN LASER DRILLING OF TITANIUM

Abstract

The use of Nd: YAG laser drilled cooling holes in the aerospace components is associated with stringent requirements. Various characteristics pertaining to the input beam, focusing lens and assist gas have to be optimized in order to produce a hole economically and of sufficient good quality at high efficiency. The work embodied in this dissertation outlines the Taguchi optimization methodology which is applied to optimize laser drilling parameters when drilling commercially pure grade Titanium of 1.5 mm thick material. An orthogonal array (OA)9 experimental design that allows to investigate the simultaneously variation of four parameters i.e. pulse energy, pulse duration, focal position and assist gas pressure having three levels was employed to evaluate the effects on efficiency and quality characteristics like drilling time and hole taper. Signal-to-Noise (S/N) ratio and ANOVA are employed to analyze the effect of laser drilling parameters on response parameters. Numerical optimization using desirability function and Genetic algorithm independently was used to optimize the process parameters for minimum drilling time and taper during laser drilling with constraints on input variables. Genetic algorithm and numerical optimization has also been used to optimize the process parameters subjected to a set of constraints on input variables, hole taper with the objective of minimizing the drilling time. Experimental runs at the optimum parameters settings were conducted to validate the results obtained from Taguchi and Numerical optimization method and Genetic algorithm. This work presents the use of neural network for modeling and optimal selection of input parameters of laser drilling process. The multi-layer perceptron (MLP) neural network model is developed using the error back-propagation training algorithm. The artificial neural network coupled with Taguchi method has been implemented. for minimizing drilling time and hole taper. The responses (SIN ratio for drilling time and taper) obtained from orthogonal array experimental design is used as train data for artificial neural networks. The accuracy of the neural network models developed in this study has been tested by comparing the simulated data with that obtained from the actual laser drilling experiments. The model results are in close agreement with the experimental results. iii The present work reports two dimensional finite element model of the heat flow pulsed laser drilling of Ti sheet. The heat transfer and parametric design capabilities of the finite element commercial software package ANSYS 7.0 are employed for this purpose. For single laser pulse heating the model calculates transient temperature profiles, thermal stresses as well as the laser drilling time for 1.5 mm thick titanium sheet. The model incorporates the temperature dependent thermo-physical properties of titanium material. Sequentially Coupled Physics Analysis, an ANSYS feature, is used where nodal temperatures from the thermal analysis are applied as body-force loads in the subsequent thermal stress analysis. The model is validated with experimentally determined laser drilling time. iv