A Special-Purpose Neural Network Recogniser to Detect Non-Random Pattern on Control Charts
With the growing employment of automatic data-collection methods and the enhancements on computerised plotting on control charts a demand exists to automate the analysis of process data. Comterised recognition techniques can provide an actual alternative to conventional methods for analysing control charts with little or no human intervention. In this paper, a neural network approach is discussed and applied to trend-pattern recognition on control charts. In the proposed approach the neural network is trained to recognise both “natural” and “unnatural” distribution of points. Experimental results are compared to a combined Shewhart-CUSUM approach in terms of Average Run Length (ARL).
KeywordsNeural Network Control Chart Unnatural Pattern Neural Network Architecture Elman Network
Unable to display preview. Download preview PDF.