A Hybrid Neural Fuzzy System for Statistical Process Control
A hybrid neural fuzzy system is proposed to monitor both process mean and variance shifts simultaneously. One of the major components of the proposed system is composed of several feedforward neural networks that are trained off-line via simulation data. Fuzzy sets are also used to provide decision-making capability on uncertain neural network output. The hybrid control chart provides an alternative to traditional statistical process control (SPC) methods. In addition, it is superior in that (1) it outperforms other SPC charts in most situations in terms of faster detection and more accurate diagnosis, and (2) it can be used in automatic production processes with minimal human intervention — a feature the other methods ignore. In this chapter, theoretical base, operations, user guidelines, chart properties, and examples are provided to assist those who seek an automatic SPC strategy.