ABSTRACT
Statistical process control charts aim to detect out-of-control signals which indicate existence of special causes effecting the process. Once such a signal is detected, the interpretation of the signal, that is, discovering the actual causes behind the signal, rests upon the shoulders of operators or engineers. Recently, some techniques have been developed for making this interpretation process easier. This study presents an overview of such techniques in three categories: traditional one-variable control charts, artificial neural network applications and
multivariate control charts.
Key Words: SPC charts, out-of-control signal, problem diagnosis
Birincil Dil | İngilizce |
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Bölüm | Architecture & City and Urban Planning |
Yazarlar | |
Yayımlanma Tarihi | 9 Ağustos 2010 |
Yayımlandığı Sayı | Yıl 2004 Cilt: 17 Sayı: 4 |