A study of Detecting the Autocorrelated Process by Variable Parameters x-bar Control Chart

• Main Authors: Shih-Han Hung, 洪士涵
• Other Authors: Chau-Chen Torng
• Format: Others
• Language: zh-TW
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/59392960850452646675

碩士 === 國立雲林科技大學 === 工業工程與管理研究所碩士班 === 95 === The traditional statistic process control uses the independent and normal data to determine whether the process has any anomalism situation. It will cause the increase of the false rate of control chart if we use the traditional independent control chart to detect the process. So it is an important issue about how to use the control chart to detect the process effectively when the autocorrelated exists in the process. So this study discusses all the control parameters and investigates the performance of the variable control parameters be used for detecting the autocorrelated process. This study divides the degree of autocorrelated into low, medium and high. No matter how the process correlation is, the VP control chart has a faster speed than the other control chart when they detect the small and medium departure of the process. For getting better detecting speed and sample cost, you should choose the bigger n1 and n2 when detecting the low autocorrelated process or small departure. The bigger control limit coefficient should be chosen when detecting the small departure. The smaller control limit coefficient should be chosen when detecting the big departure. The sample interval, samples, and the coefficient of control limit in high correlated process have no effect on the detecting speed.