On Efficient Performance Monitoring of Control Charts
To monitor process variability of products in manufacturing environments has been a challenging issue in all the times. Statistical Process Control (SPC) charts are useful to detect process variability due to specific assignable causes. The Artificial Neural Network (ANN) is also a recommended alternative to the aforementioned charting technique for detecting process parameters. This study gives attention to the use of ANN for monitoring process dispersion parameter and robust charting for location parameter using different runs rules schemes and considering the bootstrapping scenario as well.