研究生: |
高佩憶 Kao, Pei-Yi |
---|---|
論文名稱: |
監控韋伯分佈雙參數的聯合管制圖 Control Charts for Monitoring Weibull Parameters |
指導教授: |
黃榮臣
Huwang, Longcheen |
口試委員: |
樊采虹
Fan, Tsai-Hung 黃郁芬 Huang, Yu-Fen |
學位類別: |
碩士 Master |
系所名稱: |
理學院 - 統計學研究所 Institute of Statistics |
論文出版年: | 2018 |
畢業學年度: | 106 |
語文別: | 中文 |
論文頁數: | 58 |
中文關鍵詞: | 可靠度 、EWMA管制圖 、舒華特管制圖 、不偏管制圖 、韋伯分佈 、雙參數 |
外文關鍵詞: | reliability, EWMA control charts, Shewhart control charts, unbiased control chart, Weibull distribution, two parameters |
相關次數: | 點閱:2 下載:0 |
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產品的可靠度會反映出製程的技術與產品設計的優劣進而影響品牌地位,因此如何即時監控產品可靠度是工廠製造極為關注的議題。在可靠度分析中經常使用韋伯分佈來描述產品的失效時間,因此監控韋伯分佈的雙參數相當於監控產品的可靠度。在本文中提出舒華特與EWMA類型的聯合管制圖來監控韋伯分佈的雙參數,透過統計模擬的結果說明了我們所提出的舒華特管制圖大幅改善了現存舒華特管制圖監控韋伯分佈雙參數的偏差問題。所提出的EWMA管制圖不但對雙參數微小的變動有較好的監控效率,我們還可以利用估計改變點以及參數改變的診斷來幫助監控者找出製程問題的根源。最後我們利用碳纖維拉扯強度資料來詳細說明實務上如何應用所提出的舒華特和EWMA聯合管制圖來監控韋伯分佈的雙參數。
The reliability of products reflect the skills of the manufacturing process and also affect the brand reputation. Therefore, how to monitor the reliability of products in real time is an important topic in factory manufacturing. The Weibull distribution is often used to describe the product's failure time in reliability analysis. As a result, monitoring the two parameters of Weibull distribution is equivalent to monitoring the reliability of the products. In this paper, joint control charts of Shewhart and EWMA types are proposed to monitor the two parameters of Weibull distribution. The results of statistical simulation show that the proposed Shewhart control chart has greatly improved the biased phenomenon of the existing Shewhart control charts. Also, the proposed EWMA control chart has better efficiency for monitoring small shifts of the two parameters of Weibull distribution. Furthermore, we also provide the method for estimating the change point and diagnosing the shifts of the two parameters of Weibull distribution. Finally, we use an example of the breaking strength of carbon fibers to show how to apply the proposed Shewhart and EWMA joint control charts to monitor the two parameters of Weibull distribution.
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