On integration of statistical process control and engineering process control: a neural network application

摘要: In recent years the importance of quality has become increasingly apparent. Quality control in manufacturing moved from detecting non-conforming products through inspection to continuously reducing variability product performance and production process. Two existing fields which have been contributing are statistical process (SPC) engineering (EPC). past, these developed relative isolation one another, resulting engineers trained primarily classical theory almost no training statistics, data analysis noise control. On other hand, statisticians a poor understanding dynamics theory, but they excellent discrete data, design experiments methods for empirical modeling (Gupta Kumar, 1991). Both methodologies aim bring all levels their targets with minimum variability. Statistical commonly assumes that under normal conditions is driven by common causes, effect impossible or too expensive reduce, an increase unfavorable changes mean due special causes.