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An Intelligent Approach to Quality Improvement in Laser Trepan Drilling of Inconel 718 Superalloy
R. Goyal, A.K. Dubey and B.N. Upadhyay

The poor hole quality in laser percussion drilling necessitates the use of laser trepan drilling for cutting small holes in conventionally difficult to cut materials. Inconel 718, a Ni-based superalloy is a widely used aerospace material but difficult to cut by conventional methods. This paper investigates laser trepan drilling of Inconel 718 with the aim to improve cut hole quality. The experimental modelling and parametric study presented in this paper give deep insight on the effects of various input process parameters on hole geometrical features such as taper and circularity. The results of multi-objective optimization (MOO) using an artificial intelligence (AI) approach show simultaneous improvements in hole taper and circularity.

Keywords: Nd:YAG laser, Inconel 718, laser trepan drilling, multi-objective optimization (MOO), artificial intelligence (AI), artificial neural network (ANN)

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