Application of neural network for analysis out-of-control signals in multivariate manufacturing processes

Most of multivariate quality control charts are effective in detecting out-of-control signals based upon an overall statistics. The main problem of these charts is that they can not directly determine which variable or group of variables has caused the out-of-control signal and what is the magnitude of out of control. This study presents an artificial neural network-based model to supplement the multivariate 2  chart.

Keywords:

multivariate manufacturing processes , neural network , 2 chart , Statistical process control