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系統識別號 U0026-1007201202040200
論文名稱(中文) 自我相關製程能力指標在評估環境影響上之應用研究
論文名稱(英文) Developing Capability Index for Autocorrelated Data with Applications to the Evaluation of Environmental Impacts
校院名稱 成功大學
系所名稱(中) 統計學系碩博士班
系所名稱(英) Department of Statistics
學年度 100
學期 2
出版年 101
研究生(中文) 陳馥毓
研究生(英文) Fu-Yu Chen
學號 R26991119
學位類別 碩士
語文別 中文
論文頁數 75頁
口試委員 指導教授-潘浙楠
口試委員-溫敏杰
口試委員-鄭春生
口試委員-鄭順林
中文關鍵字 製程能力分析  自我相關製程能力指標  均方誤差  平均絕對值誤差率 
英文關鍵字 process capability analysis  capability indices for autocorrelated data  mean squared error  mean absolute percent error 
學科別分類
中文摘要 高度的經濟發展固然提高人類的生活水準,但其帶來的汙染卻嚴重地影響我們的生存環境,此等環境汙染問題以空氣汙染所造成之影響最為廣泛,有鑑於此,世界各國均紛紛訂定相關罰則以防止空氣汙染更進一步惡化。因此,建立客觀的環境風險評估指標以作為有效監控環境品質與事前防範的參考依據,已成為國際上追求永續發展(global sustainability)之核心課題。製程能力分析(process capability analysis, PCA)係統計製程管制(statistical process control, SPC)中的一種重要的工具。傳統的製程能力分析均假設品質特性彼此獨立,但在實際生產過程中,我們所蒐集到的資料往往會存在自我相關特性,因此,此類資料若以傳統製程能力分析的方法進行評估極易產生誤判,而導致不必要的成本浪費。本研究乃針對Sun et al. (2010) 所制定望目特性下自我相關製程能力指標之缺點進行修正,制定出一望目特性下新的及望小特性下新的自我相關製程能力指標,再利用均方誤差(mean squared error, MSE)與平均絕對值誤差率 (mean absolute percent error, MAPE)探討並與其他學者所提出之製程能力指標進行比較與分析,結果證實新自我相關製程能力指標的表現最為穩健亦較接近實際值。最後,本研究參照行政院環保署所訂定各種空氣汙染物的管制濃度,以二氧化氮與一氧化碳濃度為例,進行台灣地區空氣汙染程度之評估,研究結果可供政府決策單位及業界未來在監控環境汙染資料及評估環保表現等實務工作上之參考。
英文摘要 The economic development have caused many serious environmental problems, and thereby reduced the living quality of human beings. To reduce the environmental contamination, especially the air pollution problems, major organizations and corporations around the world start to systematically review the environmental performance of air quality of their industries based on the regulations stipulated by Environmental Protection Agency of each country. In order to prevent the environment from further deterioration contamination, the establishment of environmental risk indices for monitoring and evaluating environmental performance becomes an important research topic. Process capability analysis is a very important SPC tool for monitoring and evaluating process performance. Traditionally, Process Capability indices are developed assuming that the observations of process output are independent and follow normal distribution. However, in most cases, the process data are autocorrelated. The autocorrelated process, if mistreated as an independent process, will result in an improper decision and lead to unnecessary manufactory loss. In this paper, the novel capability indices are developed to relieve the independent assumption for nominal-the-best and smaller-the-better cases. Furthermore, we use MSE (mean squared error) and MAPE (mean absolute percent error) to compare the accuracies of our proposed indices with the existing ones. The results show that our novel capability indices are the most robust one. Finally, we use the recent NO2 and CO emission of Taiwan district as an example to evaluate the performance of air pollution. Hopefully, it can provide a useful reference for the decision maker in government and industries.
論文目次 第一章 緒論 1
1.1 研究背景與動機 1
1.2 研究目的 2
1.3 研究架構 2
第二章 文獻回顧與探討 4
2.1 時間數列 4
2.2 製程能力分析 5
2.2.1常態製程能力指標 5
2.2.2 Krishnamoorthi製程能力指標 6
2.2.3自我相關製程能力分析 7
2.2.4自我相關製程能力指標Cpmr與Cpkr 8
2.2.5自我相關製程能力指標Cpa與Cpma 9
2.3 Box-Cox 常態轉換 13
第三章 自我相關製程能力指標 14
3.1 資料檢定 14
3.2 自我相關係數顯著性 15
3.3 望目特性下之自我相關製程能力指標 16
3.4 望小特性下之自我相關製程能力指標 18
3.5 自我相關製程能力指標之模擬探討與分析 19
3.5.1製程能力指標之平均值比較 20
3.5.2製程能力指標準確性之評估標準 29
3.5.3模擬結果與分析 30
第四章 台灣地區空氣汙染實例分析 40
4.1 研究問題介紹 40
4.1.1空氣汙染之定義與來源 40
4.1.2主要空氣汙染物的種類與影響 40
4.2 空氣汙染資料簡介 43
4.3 空氣汙染資料分析與結果 45
4.3.1台灣地區二氧化氮(NO2)濃度資料分析 45
4.3.2台灣地區一氧化碳(CO)濃度資料分析 47
第五章 結論與未來研究方向 50
5.1 結論 50
5.2 未來研究方向 51
參考文獻 52
附錄A 55
附錄B 56
附錄C 66
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