Application of Artificial Neural Networks for Defect Detection in Ceramic Materials

In this study, an artificial neural network application was performed to tell if 18 plates of the same
material in different shapes and sizes were cracked or not. The cracks in the cracked plates were of
different depth and sizes and were non-identical deformations. This ANN model was developed to detect
whether the plates under test are cracked or not, when four plates have been selected randomly from
among a total of 18 ones. The ANN model used in the study is a model uniquely tailored for this study,
but it can be applied to all systems by changing the weight values and without changing the architecture
of the model. The developed model was tested using experimental data conducted with 18 plates and the
results obtained mainly correspond to this particular case. But the algorithm can be easily generalized
for an arbitrary number of items.