| Summary: | 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.
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