| Summary: | 碩士 === 立德大學 === 工業管理研究所 === 96 === The averages and variances are usually controlled while dealing with quality characteristics.
In the event of controlling averages，X control chart is commonly used.X control chart is mainly applied to control the averages of quality characteristics.shown in manufacturing process. However, X control chart is quite sensitive to variation of values. Changes are clearly shown in a control chart.Unstable conditions of manufacturing process thus can be observed which leads to proper adjustments for bringing the process back to its normal conditions.Meanwhile,extreme values have little impact on x control chart because medians are used here.As a result,x control chart cannot immediately react to initial unstable conditions of manufacturing process.
Due to the above reason,this study tempts to use Smooth Adaptive Estimator〈hereinafter referred to as SAE〉by combining Bpptstrap technique to estimate the averages and variances in the manufacturing process.Furthermore,three SAE confidence intervals including Standard Bootstrap,Percentile Bootstrap and Biased-Corrected Percentile Bootstrap are established.Finally,the advantages of SAE confidence interval,Shewhart Control Chart the supervisory ability of X and x are explored and discussed.
After using Matlab program for simulation,the result discovered that SAE in supervises the control regulation aspect,besides in normal distribution's process regulation small sample sampling examination by X,x more suitable use,SAE to be possible the keen discovery process regulation variation,and is suitable
in the process regulation big sample and the small sample sampling examination,and works as when the process regulation the sharing condition is different, receives the influence small which compared to X, X will come,
may reduce the extreme value to monitor ability the influence.
|
|---|
