  Machine learning which is a sub-domain of an Artificial Intelligence which is
finding various applications in manufacturing and material science sectors. In
the present study, Deep Generative Modeling which a type of unsupervised
machine learning technique has been adapted for the constructing the artificial
microstructure of Aluminium-Silicon alloy. Deep Generative Adversarial Networks
has been used for developing the artificial microstructure of the given
microstructure image dataset. The results obtained showed that the developed
models had learnt to replicate the lining near the certain images of the
microstructures.
