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  1. NTU Theses and Dissertations Repository
  2. 公共衛生學院
  3. 公共衛生碩士學位學程
請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65994
完整後設資料紀錄
DC 欄位值語言
dc.contributor.advisor吳章甫
dc.contributor.authorKa-Chon Ngen
dc.contributor.author吳嘉駿zh_TW
dc.date.accessioned2021-06-17T00:18:16Z-
dc.date.available2020-03-12
dc.date.copyright2020-03-12
dc.date.issued2020
dc.date.submitted2020-02-13
dc.identifier.citation1 國家發展委員會: 臺灣經濟發展歷程與策略(2018).
2 行政院主計總處: 行業標準分類(第10次修訂)(2016).
3 Bender, T.J., C. Beall, H. Cheng, R.F. Herrick, A.R. Kahn, R. Matthews et al.: Cancer incidence among semiconductor and electronic storage device workers. Occup Environ Med 64(1): 30-36 (2007).
4 Kim, M.H., H. Kim, and D. Paek: The health impacts of semiconductor production: an epidemiologic review. Int J Occup Environ Health 20(2): 95-114 (2014).
5 謝功毅: 半導體員工生殖健康及癌症風險之探討(2005).
6 Lee, C., S.K. Kang, H. Kim, and I. Kim: Background and Activities of the Samsung Ombudsperson Commission in Korea. J Prev Med Public Health 52(4): 265-271 (2019).
7 張振平、宋隆佑、朱振群、林宜長: 半導體廠維修作業勞工有害氣體溢散調查. 勞工安全衛生研究季刊 第8卷第2期(2000年6月).
8 張建新: 半導體機台設備維護保養時之局部排氣改善研究(2003).
9 AIHA: A Strategy for Assessing and Managing Occupational Exposures, 4th edition(2015).
10 魏文慈、陳春盛: 以相似暴露族群分析方法建立某LED廠暴露實態. 工業安全衛生月刊 (2011).
11 勞動部職業安全衛生署: 化學品評估及分級管理 健康危害化學品-定量暴露評估推估模式.
12 AIHA Exposure Assessment Committee, A.: Mathematical Models for Estimating Occupational Exposure to Chemicals(2000/12/1).
13 Nicas, M.: Estimating exposure intensity in an imperfectly mixed room. Am Ind Hyg Assoc J 57(6): 542-550 (1996).
14 Furtaw, E.J., Jr., M.D. Pandian, D.R. Nelson, and J.V. Behar: Modeling indoor air concentrations near emission sources in imperfectly mixed rooms. J Air Waste Manag Assoc 46(9): 861-868 (1996).
15 Jayjock, M.A., T. Armstrong, and M. Taylor: The Daubert Standard as Applied to Exposure Assessment Modeling Using the Two-Zone (NF/FF) Model Estimation of Indoor Air Breathing Zone Concentration as an Example. Journal of Occupational and Environmental Hygiene 8(11): D114-D122 (2011).
16 Spencer, J.W., and M.J. Plisko: A comparison study using a mathematical model and actual exposure monitoring for estimating solvent exposures during the disassembly of metal parts. J Occup Environ Hyg 4(4): 253-259 (2007).
17 Arnold, S.F., Y. Shao, and G. Ramachandran: Evaluation of the well mixed room and near-field far-field models in occupational settings. J Occup Environ Hyg 14(9): 694-702 (2017).
18 Arnold, S.F., Y. Shao, and G. Ramachandran: Evaluating well-mixed room and near-field-far-field model performance under highly controlled conditions. J Occup Environ Hyg 14(6): 427-437 (2017).
19 Boelter, F.W., C.E. Simmons, L. Berman, and P. Scheff: Two-zone model application to breathing zone and area welding fume concentration data. J Occup Environ Hyg 6(5): 298-306 (2009).
20 Gaffney, S., E. Moody, M. McKinley, J. Knutsen, A. Madl, and D. Paustenbach: Worker exposure to methanol vapors during cleaning of semiconductor wafers in a manufacturing setting. J Occup Environ Hyg 5(5): 313-324 (2008).
21 Jayjock, M., P. Logan, B. Mader, J. Owens, J. Eldridge, M. Costello et al.: Modeled comparisons of health risks posed by fluorinated solvents in a workplace spill scenario. Ann Occup Hyg 55(2): 202-213 (2011).
22 Sahmel, J., K. Unice, P. Scott, D. Cowan, and D. Paustenbach: The use of multizone models to estimate an airborne chemical contaminant generation and decay profile: occupational exposures of hairdressers to vinyl chloride in hairspray during the 1960s and 1970s. Risk Anal 29(12): 1699-1725 (2009).
23 經濟部工業局: 化學品暴露評估與分級管理手冊(2018).
24 Pamela R.D. Williams, T.A., Daniel Drolet: Introduction to IH MOD 2.0 (2018).
25 Baldwin, P.E., and A.D. Maynard: A survey of wind speeds in indoor workplaces. Ann Occup Hyg 42(5): 303-313 (1998).
26 高馨儀: 晶圓廠離子植入機台維修作業化學性因子暴露研究(1999).
27 古坤文: 半導體金屬蝕刻機台於預防維修時之污染物逸散控制(2003).
28 高耀嵐: 彩色濾光片廠揮發性有機氣體控制與改善研究(2009).
29 Ganser, G.H., and P. Hewett: Models for nearly every occasion: Part II - Two box models. J Occup Environ Hyg 14(1): 58-71 (2017).
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65994-
dc.description.abstract半導體在製程及研發上使用多種類之新興化學品,特別是混合物,引起對作業暴露危害的關注及增加管理的複雜性。在實務進行大規模作業環境監測有其困難處,且具標準採樣分析及容許濃度之化學品有限,人員潛在危害可能被忽略。本實習研究基於AIHA暴露評估架構,研究目的是1. 整理事業單位之數據資料庫,以描述性統計分析2015-2018/9化學品使用量及含IARC致癌物質化學品數量,鑑定使用含IARC致癌物質化學品之暴露族群(定義為風險相似暴露族群);2. 應用定量暴露模型—二暴露區模型,推估設備維修保養作業人員丙酮之暴露濃度,與實測值及法規容許濃度比較,評估其實務普及應用之可能性。事業單位共使用21797件化學品並篩選出1135件含IARC物質之化學品,並鑑定出120個有使用之相似暴露族群;使用軟體AIHA IH MOD 2.0進行二暴露區模型分析,人員呼吸帶之暴露濃度peak值為31.7 ppm,與現場實際測量濃度9.75 ppm高3.25倍,落在合理的預測範圍;另以風險管理角度調整參數,呼吸帶之暴露濃度peak值可能在15.83 – 55.99 ppm之間,而時量平均值在12.71-41.17 ppm之間。本研究以定性方式鑑定風險相似暴露族群,能深入了解化學品之致癌物質、種類及所使用的族群,實務管理上提供優先關注及健康追蹤,而二暴露區模型提供合理而保守的推估值,並在多重條件估算下peak值及時量平均都遠低於我國法規值200 ppm,加上其操作簡單便利、具科學性及低成本,因此本研究之結果支持兩者在化學品實務管理的應用。zh_TW
dc.description.abstractUsing a variety of chemicals, especially emerging agents and mixtures, in semiconductor industries has raised concerns for potential exposure hazards and management complexity. There are difficulties in carrying out large-scale exposure monitoring of chemical agents. Meanwhile, chemicals with standard sampling analysis and permissible exposure limit are limited, as such the potential hazards of workers may be underestimated. This internship study is based on the AIHA exposure assessment framework. The purpose of the study is to: 1. Compile the databases and descriptively analyze the use of chemicals between 2015-2018/9, focusing on those containing IARC carcinogens and identifying the number of risk SEGs (defined as similar risk exposure groups using chemicals containing IARC carcinogens); 2. Apply the two-zone model to estimate the exposure concentration of acetone for preventive and maintenance workers and compare with the measured values ​​and permissible exposure limit. The company used a total of 21,797 chemicals, included 1,135 chemicals containing IARC chemicals, and 120 risk SEGs; AIHA IH MOD 2.0 software was used to perform quantitative modeling analysis. The estimated peak value is 31.7 ppm, which is 3.25 times higher than the measured concentration of 9.75 ppm, and falls within a reasonable prediction. In addition, several parameters are adjusted in the perspective of risk management. The peak value of the revised estimates ranges between 15.83-55.99 ppm, and time-weighted average (TWA) ranged between 12.71-41.17 ppm. Qualitative identification of risk SEGs can provide insights into the carcinogens, types, and exposure groups, providing prioritization for exposure and health managements. The two-zone model provides reasonable and conservative estimates. Under multiple scenarios, the concentration peak and TWA of acetone are below the permissible exposure limit of 200 ppm. This model is user-friendly, scientifically proven and low-cost. The results of this study support the application of these two approaches for chemical management in practice.en
dc.description.provenanceMade available in DSpace on 2021-06-17T00:18:16Z (GMT). No. of bitstreams: 1
ntu-109-R05847029-1.pdf: 6843520 bytes, checksum: 5e82ade6cebb991d74f8ce0d776d45f3 (MD5)
Previous issue date: 2020
en
dc.description.tableofcontents目 錄
誌謝 i
中文摘要 ii
Abstract iii
圖目錄 iv
表目錄 v
名詞解譯 vi
第一章 前言 1
1.1 研究緣起 1
1.2 研究目的 1
第二章 文獻探討 2
2.1 國內半導體產業歷程、現況及未來發展趨勢 2
2.2 半導體產業化學品暴露之流行病學及健康危害 4
2.3 相似暴露族群 8
2.4 定量推估模式 8
第三章 研究方法 13
3.1 研究架構與流程 13
3.2 風險相似暴露族群鑑定之資料搜集及分析方法 15
3.2 定量推估模式之資料搜集、分析方法及參數說明 18
第四章 結果與討論 26
4.1 風險相似暴露族群之鑑定 26
4.2 定量推估模式之評估結果 33
4.3 風險角度調整參數: 化學品使用量減半、暴露時間減半及換氣量敏感度分析 36
第五章 結論 41
附錄一 42
使用Microsoft Excel 進行風險SEG之鑑定
附錄二 49
使用定量推估模型估算設備維修保養人員使用丙酮時化學品暴露情況
風險角度調整參數:化學品使用量減半、暴露時間減半及換氣量敏感度分析
附錄三 56
設備預防保養作業FTIR儀器實際監測結果,2018/11/27、2018/12/07、2018/12/13及2019/3/27共四次完整量測數據結果
附錄四 60
實習單位及實習內容簡介
參考文獻 62
dc.language.isozh-TW
dc.subject暴露評估zh_TW
dc.subject定量推估模型zh_TW
dc.subject相似暴露族群zh_TW
dc.subject二暴露區模型半導體製程zh_TW
dc.subjectsimilar exposure groupsen
dc.subjectexposure assessmenten
dc.subjectquantitative modelingen
dc.subjecttwo- zone exposure model semiconductor industryen
dc.title風險相似暴露族群鑑定及定量推估模型應用-以半導體廠為例zh_TW
dc.titleIdentification of Risk Similar Exposure Groups and Application of Quantitative Modeling - A Semiconductor manufacturing industryen
dc.typeThesis
dc.date.schoolyear108-1
dc.description.degree碩士
dc.contributor.coadvisor曹永杰
dc.contributor.oralexamcommittee楊孝友
dc.subject.keyword相似暴露族群,暴露評估,定量推估模型,二暴露區模型半導體製程,zh_TW
dc.subject.keywordsimilar exposure groups,exposure assessment,quantitative modeling,two- zone exposure model semiconductor industry,en
dc.relation.page63
dc.identifier.doi10.6342/NTU202000456
dc.rights.note有償授權
dc.date.accepted2020-02-13
dc.contributor.author-college公共衛生學院zh_TW
dc.contributor.author-dept公共衛生碩士學位學程zh_TW
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