A Study of Process Capability Indices for Second-order Autoregressive Processes

• Main Authors: Szu-Chi Ho, 何思祺
• Other Authors: Tong-Yuan Koo
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/38759250346046680789

碩士 === 國立雲林科技大學 === 工業工程與管理系 === 102 === With the progress of technology and improvement of living standards, customers select products will consider the quality in addition to the price. In addition to the emphasis of productivity, manufacturer must also pay attention to quality. Process capability indexare useful tools in realizing the performance of processand improving process. The process data are usually assumed independent when using the process capability index typically. However, process data are often autocorrelated in industrial application. If ignore the autocorrelation of data, the process capability index will not accurately represent the ability of the process. Mohamadi et al. (2011) presented the multivariate regression model to modify process capability estimated from classical method, where AR (1) parameters are utilized as regression explanatory variables. In this paper, the effect of autocorrelation on process capability index when data are produced by an autoregressive model of order two and the performance of the presented method will be investigated using Monte Carlo simulation. The results show that autocorrelation coefficient and starting value of second-order autoregressive process will affect the process capability index.