Applying Filter design Approach to Statistical Process Control for Lewis’s ARMA Model

碩士 === 國立中央大學 === 工業管理研究所 === 99 === In this study, we apply filter design to statistical process control (SPC) and discuss the impact of different process distributions. Instead of using conventional autoregressive moving-average processes, we assume Lewis’s autoregressive moving-average (ARMA) pro...

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Main Authors: Jhe-hung Yeh, 葉哲宏
Other Authors: Ying-chieh Yeh
Format: Others
Language:en_US
Published: 2011
Online Access:http://ndltd.ncl.edu.tw/handle/32261600602820359382
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spelling ndltd-TW-099NCU050410652015-10-19T04:03:05Z http://ndltd.ncl.edu.tw/handle/32261600602820359382 Applying Filter design Approach to Statistical Process Control for Lewis’s ARMA Model 在Lewis的ARMA模型下 校正器的設計方法運用在統計製程控制上 Jhe-hung Yeh 葉哲宏 碩士 國立中央大學 工業管理研究所 99 In this study, we apply filter design to statistical process control (SPC) and discuss the impact of different process distributions. Instead of using conventional autoregressive moving-average processes, we assume Lewis’s autoregressive moving-average (ARMA) processes as data processes. The control chart we used in this study is the exponentially weighted moving average (EWMA) control chart. We will apply linear filter on the observations generated from our data process to obtain our control chart statistic. With the control chart statistic, we can calculate the out-of-control ARL by Markov chain method. And our research objective is to reduce the out-of-control ARL with a predetermined in-control ARL. In the final, we adjust parameter and transform distribution to propose a relatively simple algorithm. Therefore, we can avoid complex and time-consuming calculation. Ying-chieh Yeh 葉英傑 2011 學位論文 ; thesis 29 en_US
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description 碩士 === 國立中央大學 === 工業管理研究所 === 99 === In this study, we apply filter design to statistical process control (SPC) and discuss the impact of different process distributions. Instead of using conventional autoregressive moving-average processes, we assume Lewis’s autoregressive moving-average (ARMA) processes as data processes. The control chart we used in this study is the exponentially weighted moving average (EWMA) control chart. We will apply linear filter on the observations generated from our data process to obtain our control chart statistic. With the control chart statistic, we can calculate the out-of-control ARL by Markov chain method. And our research objective is to reduce the out-of-control ARL with a predetermined in-control ARL. In the final, we adjust parameter and transform distribution to propose a relatively simple algorithm. Therefore, we can avoid complex and time-consuming calculation.
author2 Ying-chieh Yeh
author_facet Ying-chieh Yeh
Jhe-hung Yeh
葉哲宏
author Jhe-hung Yeh
葉哲宏
spellingShingle Jhe-hung Yeh
葉哲宏
Applying Filter design Approach to Statistical Process Control for Lewis’s ARMA Model
author_sort Jhe-hung Yeh
title Applying Filter design Approach to Statistical Process Control for Lewis’s ARMA Model
title_short Applying Filter design Approach to Statistical Process Control for Lewis’s ARMA Model
title_full Applying Filter design Approach to Statistical Process Control for Lewis’s ARMA Model
title_fullStr Applying Filter design Approach to Statistical Process Control for Lewis’s ARMA Model
title_full_unstemmed Applying Filter design Approach to Statistical Process Control for Lewis’s ARMA Model
title_sort applying filter design approach to statistical process control for lewis’s arma model
publishDate 2011
url http://ndltd.ncl.edu.tw/handle/32261600602820359382
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