A Study of Auto-correlated Process Control Chart From the C Chemical Factory

• Main Authors: Che-Chang Kuo, 郭哲彰
• Other Authors: 陳雲岫
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/39778247015734147684

碩士 === 元智大學 === 工業工程與管理學系 === 99 === The statistical process control was usually based on the assumptions of normality and independence. However, the observations from the process are often against such assumptions and show auto-correlation in many situations, such as continuous process of chemical industry and auto-inspection process with shorter sampling intervals. The typical effect of auto-correlated process using traditional control chart was the decrease of average run length, which results in higher false alarm rates. This study aimed to investigate methodologies for improving the performance of the individual control chart from the C factory, which observations were fitting AR (1) model. We found that the residue based control charts have higher type Ⅱ error when the abnormal behavior is successive. Montgomery and Mastrangelos’ MCEWMA chart can solve the problems of fitting complicated ARIMA model through choosing appropriate λ , but it is hard to practice in reality since the control limit is variable. Wheeler and Gilbert adjusted control limits are easier to use, they can be used in existing frame. The simulation result shows that performance of Gilbert’s control chart is better than Wheelers’, but they are not suit for high level auto-correlated process. The C factory process is moderately auto-correlated, therefore, we suggest using Gilbert’s control chart instead of Shewhart individual control chart to decrease false alarm rates and detect assignable causes appropriately.