Defect prediction with neural networks
R. Stites, Bryan Ward, Robert V. Walters · 1991
The industrial and scientific world abound with problems that are poorly un&rstood or for which apparent anomalous conditions exist.Artificial Neural Networks are utilized with conventional techniques to extract salient features and relationships which are non-linear in nature.Defect causality in a large continuous flow chemical process is investigated.Significant gains in the prediction of defects over traditional statistical methods are achieved.