Marengo Emilio, Gennaro Maria Carla, Gianotti Valentina, Robotti Elisa
Dipartimento di Scienze e Tecnologie Avanzate, Università del Piemonte Orientale, Spalto Marengo 33, 15100 Alessandria, Italy.
Ann Chim. 2003 May-Jun;93(5-6):525-38.
The control and monitoring of an industrial process is performed in this paper by the multivariate control charts. The process analysed consists of the bottling of the entire production of 1999 of the sparkling wine "Asti Spumante". This process is characterised by a great number of variables that can be treated with multivariate techniques. The monitoring of the process performed with classical Shewhart charts is very dangerous because they do not take into account the presence of functional relationships between the variables. The industrial process was firstly analysed by multivariate control charts based on Principal Component Analysis. This approach allowed the identification of problems in the process and of their causes. Successively, the SMART Charts (Simultaneous Scores Monitoring And Residual Tracking) were built in order to study the process in its whole. In spite of the successful identification of the presence of problems in the monitored process, the Smart chart did not allow an easy identification of the special causes of variation which casued the problems themselves.
本文采用多元控制图对工业过程进行控制和监测。所分析的过程是1999年“阿斯蒂起泡酒”整个生产过程的装瓶环节。该过程的特点是有大量变量，可采用多元技术进行处理。用传统的休哈特控制图对该过程进行监测非常危险，因为它们没有考虑变量之间的函数关系。首先通过基于主成分分析的多元控制图对该工业过程进行分析。这种方法能够识别过程中的问题及其原因。随后，构建了SMART图（同步得分监测与残差跟踪）以便对整个过程进行研究。尽管成功识别出了监测过程中存在的问题，但SMART图并不能轻松识别导致这些问题的特殊变异原因。
