Process-Monitoring-for- Quality — A Model Selection Criterion for Shallow Neural Networks

Abstract

Since most manufacturing systems generate only a fewdefects per million of opportunities, rare quality eventdetection is one of the main applications of process monitoringfor quality. Single-hidden-layer feed-forwardneural networks have been successfully applied to performthis task. However, since the best network structureis not known in advance, many models need to be learnedand tested to select a final model with the right numberof hidden neurons. A new three-dimension 3D