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系統識別號 U0026-1807201423301200
論文名稱(中文) 建立一個應用於非常態分配多變量資料之管制圖
論文名稱(英文) An AK-chart for Non-Normal Data
校院名稱 成功大學
系所名稱(中) 工業與資訊管理學系
系所名稱(英) Department of Industrial and Information Management
學年度 102
學期 2
出版年 103
研究生(中文) 劉嘉豪
研究生(英文) Chia-Hau Liu
學號 R36014074
學位類別 碩士
語文別 中文
論文頁數 59頁
口試委員 指導教授-王泰裕
口試委員-施勵行
口試委員-陳梁軒
口試委員-謝中奇
中文關鍵字 多變量管制圖  非常態分配  適應性管制圖  類神經網路 
英文關鍵字 Multivariate control chart  statistical process control  one-class classification method 
學科別分類
中文摘要 管制圖為現代企業常用來監控製程的工具之一,而當製程有多個品質特性且其之間具有相關性時,則以多變量管制圖為主要的監控工具。現有的多變量管制圖大部分都須在品質特性為常態分配情境下才能使用,然而在現實中許多製程的品質特性不一定符合此假設,這樣的製程無法使用傳統多變量管制圖,需要使用多變量無母數管制圖來進行監控,但至今這類型的管制圖仍有許多問題,其中,多變量核域距離管制圖能在複雜情境下監控製程且針對大幅度偏移有良好的偵測效果,但針對中小幅度偏移的偵測能力較差,且現有設計方法很難被管理者了解。適應性管制是能改善管制圖中小幅度偏移偵測能力的技術,而本研究利用適應性管制技術以及改變多變量核域距離管制圖設計方法建構出適應性多變量核域距離管制圖,克服先前管制圖建構困難以及中小幅度偏移偵測的問題,並結合原先能在複雜環境監控以及快速偵測大幅度偏移的優勢建構出能在品質特性為非常態分配製程下具備優良偵測能力的多變量管制圖。最後,本研究利用非常態管制圖實驗以及案例資料對適應性多變量核域距離管制圖進行分析比較,發現在多變量常態分配以及峰度偏離多變量t分配的情境下適應性多變量核域距離管制圖能較原先的多變量核域距離管制圖更加快速偵測出製程的偏移,且在中小幅度偏移時改善的效果最為明顯,然而在偏度及峰度同時偏離的品質特性分配情境下,由於本身管制界限的建構方式,使得適應性多變量核域距離管制圖對偵測能力的改善沒有明顯的效果。最後,本研究利用面板薄膜生成製程的資料來針對管制圖進行評估,發現適應性多變量核域距離管制圖與多變量核域距離管制圖都能在這個情境下快速偵測出異常,且適應性多變量核域距離管制圖針對小幅度偏移較多變量核域距離管制圖來的快速。
英文摘要 Traditional multivariate control charts assume that measurement from manufacturing processes follows a multivariate normal distribution. However, this assumption may not hold or may be difficult to verify because not all the measurements from manufacturing processes are normally distributed in practice. This study develops a new multivariate control chart for monitoring the processes with non-normal data. We propose a mechanism based on integrating the one-class classification method and the adaptive technique. The adaptive technique is used to improve the sensitivity to small shift on one-class classification in statistical process control. In addition, this design provides an easy way to allocate the value of type I error so it is easier to be implemented. Finally, the simulation study and the real data from industry are used to demonstrate the effectiveness of the proposed control charts.
論文目次 摘要 ii
英文摘要 iii
致謝 viii
表目錄 xi
圖目錄 xii
符號表 xiii
第一章 緒論 1
第一節 研究背景與動機 1
第二節 研究目的 2
第三節 研究範圍與限制 3
第四節 研究流程 3
第五節 論文架構 4
第二章 文獻探討 5
第一節 多變量管制圖 6
第二節 適應性管制圖 10
第三節 類神經網路 15
第四節 多變量核域距離管制圖(K-chart) 23
第五節 小結 25
第三章 適應性多變量核域距離管制圖 26
第一節 適應性多變量核域距離管制圖建構流程 26
第二節 資料前處理 27
第三節 建構支援向量資料描述 28
第四節 基因演算法最佳化管制參數 32
第五節 監控模式建構 35
第六節 評估指標 36
第七節 小結 36
第四章 模式分析 37
第一節 模擬實驗情境 37
第二節 AK-chart 41
第三節 管制圖表現評估 42
第四節 案例分析 49
第五節 小結 50
第五章 結論與建議 51
第一節 結論 51
第二節 後續研究建議與方向 52
參考文獻 53
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