Abstract
Polymer composites are finding substantial application in the most diverse engineering fields. Drilling in composites is an unavoidable operation which leads to substantial damage around the drilled hole. Conventional regression techniques have been used to develop models for drilling forces and drilling-induced damage. The present trend is towards the use of soft computing techniques for development of predictive models. This chapter briefly reviews the state-of-the-art concepts of soft computing techniques, namely artificial neural network (ANN), genetic algorithm (GA) and particle swarm optimisation (PSO). The application of these techniques for developing optimised, generic predictive models for drilling forces and drilling-induced damage has also been highlighted.
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