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  1. NTU Theses and Dissertations Repository
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請用此 Handle URI 來引用此文件: http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79989
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dc.contributor.advisor周雍強(Yon-Chun Chou)
dc.contributor.authorChyau-Huey Kuoen
dc.contributor.author郭喬卉zh_TW
dc.date.accessioned2022-11-23T09:19:54Z-
dc.date.available2021-08-10
dc.date.available2022-11-23T09:19:54Z-
dc.date.copyright2021-08-10
dc.date.issued2021
dc.date.submitted2021-07-21
dc.identifier.citation[1]Becker, J., Delfmann, P., Dietrich, H. A., Steinhorst, M., Eggert, M. (2016). Business process compliance checking–applying and evaluating a generic pattern matching approach for conceptual models in the financial sector. Information Systems Frontiers, 18(2), 359-405. [2]Bolasco, S., Canzonetti, A., Capo, F. M., Della Ratta-Rinaldi, F., Singh, B. K. (2005). Understanding text mining: A pragmatic approach. In Knowledge mining (pp. 31-50). Springer, Berlin, Heidelberg.. [3]Bruckner, D., Zeilinger, H., Dietrich, D. (2011). Cognitive automation — Survey of novel artificial general intelligence methods for the automation of human technical environments. IEEE Transactions on Industrial Informatics, 8(2), 206-215. [4]Cabanillas Macías, C., Resinas Arias de Reyna, M., Ruiz Cortés, A. (2010). Hints on how to face business process compliance. III Taller De Procesos De Negocio E Ingeniería De Servicios, PNIS2010, Valencia, España. [5]Chapman, C. (2020). Commentary: Mind Your Text in Marketing Practice. Journal of Marketing, 84(1), 26-31. [6]Comaniciu, D., Ramesh, V., Meer, P. (2003). Kernel-based object tracking. IEEE Transactions on pattern analysis and machine intelligence, 25(5), 564-577.. [7]Elgammal, A., Turetken, O., van den Heuvel, W. J., Papazoglou, M. (2016). Formalizing and appling compliance patterns for business process compliance. Software Systems Modeling, 15(1), 119-146. [8]Fan, W., Wallace, L., Rich, S., Zhang, Z. (2006). Tapping the power of text mining. Communications of the ACM, 49(9), 76-82. [9]Fasth, Å., Stahre, J. (2010, June). Concept model towards optimising Levels of Automation (LoA) in assembly systems. In Proceedings of the 3rd CIRP Conference on Assembly Technologies and Systems (pp. 1-3). [10]Gupta, V., Lehal, G. S. (2009). A survey of text mining techniques and applications. Journal of emerging technologies in web intelligence, 1(1), 60-76.. [11]Hallikainen, P., Bekkhus, R., Pan, S. L. (2018). How OpusCapita Used Internal RPA Capabilities to Offer Services to Clients. MIS Quarterly Executive, 17(1).. [12]Hashmi, M., Governatori, G., Lam, H. P., Wynn, M. T. (2018). Are we done with business process compliance: state of the art and challenges ahead. Knowledge and Information Systems, 57(1), 79-133. [13]Heinrich, H. W. (1931). Industrial Accident Prevention: A Scientific Approach McGraw-Hill. New York. [14]Helm, J. M., Swiergosz, A. M., Haeberle, H. S., Karnuta, J. M., Schaffer, J. L., Krebs, V. E., ... Ramkumar, P. N. (2020). Machine learning and artificial intelligence: Definitions, applications, and future directions. Current reviews in musculoskeletal medicine, 13(1), 69-76. [15]Hofmann, P., Samp, C., Urbach, N. (2020). Robotic process automation. Electronic Markets, 30(1), 99-106. [16]Iguernaissi, R., Merad, D., Aziz, K., Drap, P. (2019). People tracking in multi-camera systems: a review. Multimedia Tools and Applications, 78(8), 10773-10793. [17]Kok, J. N., Boers, E. J., Kosters, W. A., Van der Putten, P., Poel, M. (2009). Artificial intelligence: definition, trends, techniques, and cases. Artificial intelligence, 1, 270-299. [18]Kothiya, S. V., Mistree, K. B. (2015, January). A review on real time object tracking in video sequences. In Electrical, Electronics, Signals, Communication and Optimization (EESCO), 2015 International Conference on (pp. 1-4). [19]Krogstie, J. (2016). Quality of business process models. In Quality in Business Process Modeling (pp. 53-102). Springer, Cham. [20]Leopold, H., van der Aa, H., Reijers, H. A. (2018). Identifying candidate tasks for robotic process automation in textual process descriptions. In Enterprise, business-process and information systems modeling (pp. 67-81). Springer, Cham.. [21]Ng, K. K., Chen, C. H., Lee, C. K. M., Jiao, J. R., Yang, Z. X. (2021). A systematic literature review on intelligent automation: Aligning concepts from theory, practice, and future perspectives. Advanced Engineering Informatics, 47, 101246. [22]Radke, R. J. (2010). A survey of distributed computer vision algorithms. In Handbook of Ambient Intelligence and Smart Environments (pp. 35-55). Springer, Boston, MA.. [23]Reddy, K. N., Undavalli Harichandana, T. A., Rajesh, S. M. (2019). A Study of Robotic Process Automation Among Artificial Intelligence. International Journal of Scientific and Research Publications (IJSRP), 9(2). [24]Sadiq, S., Governatori, G., Namiri, K. (2007, September). Modeling control objectives for business process compliance. In International conference on business process management (pp. 149-164). Springer, Berlin, Heidelberg. [25]Suri, V. K., Elia, M. D., Arora, P., van Hillegersberg, J. (2018, February). Automation of knowledge-based shared services and centers of expertise. In International Workshop on Global Sourcing of Information Technology and Business Processes (pp. 56-75). Springer, Cham.. [26]Thurman, D. A., Brann, D. M., Mitchell, C. M. (1997, October). An architecture to support incremental automation of complex systems. In 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation (Vol. 2, pp. 1174-1179). IEEE.. [27]Tiwari, M., Singhai, R. (2017). A review of detection and tracking of object from image and video sequences. Int. J. Comput. Intell. Res, 13(5), 745-765. [28]Van der Aalst, W. M. (2013). Business process management: a comprehensive survey. International Scholarly Research Notices, 2013. [29]Wang, Y., Lu, K., Zhai, R. (2014, October). Challenge of multi-camera tracking. In 2014 7th International Congress on Image and Signal Processing (pp. 32-37). IEEE.. [30]Willcocks, L. P., Lacity, M., Craig, A. (2015). The IT function and robotic process automation. [31]林昀。鳳山站車停後又開,導致4人跌出車外【上報快訊】民108年11月8日,取自https://www.upmedia.mg/news_info.php?SerialNo=75010。 [32]胡順惠。中油未依SOP又出包!桃機還原「漏油經過」:今年3起且隱匿未報【ETtoday新聞雲】民109年10月25日,取自:https://www.ettoday.net/news/20191025/1564984.htm?redirect=1。 [33]陳偉業、陳柏君、陳柏安、劉定一、王穆衡、翁美娟、史習平. (2007). 商用運輸系統智慧化整體研究發展計畫—商用車輛智慧化車上單元設備需求調查、系統整合模組規劃及研發(第二期)。 [34]提升勞工安全行為及認知,作業安全更有保障。【勞動部職業安全衛生署】民108年12月9日,取自:https://tmsc.osha.gov.tw/news2cont.asp?kk=2875 [35]葉明華. (2006). 考試贏家. 思達迪國際有限公司.
dc.identifier.urihttp://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79989-
dc.description.abstract標準作業流程可以提高生產速率以及產品品質的齊一性,但卻不能確保生產時的每一個操作步驟都能如期運行,許多意外的發生原因,不外乎是因為操作人員一時疏忽、過度疲勞或是貪圖方便,而隨意的簡化操作步驟,沒有確實遵守標準作業流程的步驟進行。 即使是現今許多自動化工廠,仍然使用傳統的人力辨識、判斷監控影像,以檢驗標準作業流程順應性,然而傳統的人力監控除了耗用大量的人力與精神外,監控的範圍與效用也相對有限,相較於機器,人會有怠惰、疲勞、注意力不集中的問題,所以往往無法及時發現漏洞,導致財產或是安全上的損失。 因此,本研究期望發展出一個限制滿足模型,運用影像辨識技術輔助檢驗標準作業流程,將原本一連貫的作業流程拆解成小單元的動作,並透過影像辨識資料的轉換,發展能夠適用於各種不同流程結構的檢驗模型,偵測作業流程是否出現環境缺失、物件缺失等違反標準作業流程的情境發生,並針對違反標準作業流程的情況提前預警,在生產上能減少重工的機會;在安全上能減少意外發生,給予使用者安全無虞的工作環境。zh_TW
dc.description.provenanceMade available in DSpace on 2022-11-23T09:19:54Z (GMT). No. of bitstreams: 1
U0001-2107202113391600.pdf: 2920573 bytes, checksum: 9b2202bcc31b94895c066aeca4bd296a (MD5)
Previous issue date: 2021
en
dc.description.tableofcontents誌謝............................................................................... i 摘要.............................................................................. ii ABSTRACT ........................................................................ iii 目錄.............................................................................. iv 圖目錄............................................................................ vi 表目錄........................................................................... vii Chapter 1 緒論 .................................................................... 1 1.1 問題背景....................................................................... 1 1.2 問題分析....................................................................... 2 1.3 研究目的....................................................................... 3 1.4 研究範圍與限制.................................................................. 5 1.5 研究流程....................................................................... 5 Chapter 2 文獻探討 ................................................................ 6 2.1 自動化......................................................................... 6 2.1.1 機械性流程自動化 ............................................................. 7 2.1.2 智慧自動化 .................................................................. 7 2.1.3 認知自動化 .................................................................. 8 2.1.4 人工智慧 .................................................................... 8 2.2 業務流程管理................................................................... 10 2.3 業務流程順應性................................................................. 11 2.4 業務流程模型和標記法............................................................ 13 2.4.1 流物件 ..................................................................... 14 2.4.2 連接物件 ................................................................... 15 2.4.3 泳道(Swim lanes) .......................................................... 16 2.4.4 器物(Artifacts)............................................................ 16 2.5 文本分析...................................................................... 17 2.6 電腦監控與追蹤................................................................. 20 Chapter 3 研究模型建構 ............................................................ 23 3.1 研究模型概述................................................................... 23 3.2 常態形式流程模型............................................................... 24 3.3 各種活動關係的模型定義.......................................................... 26 3.4 常見違反標準作業流程之情境分析.................................................. 35 Chapter 4 數值分析 ............................................................... 41 4.1 LINGO實作 .................................................................... 41 4.1.1 偵測作業流程是否有遺漏 ........................................ ...............41 4.1.2 偵測作業順序是否被更改 ....................................................... 43 4.1.3 偵測作業流程是否出現瓶頸 ..................................................... 53 4.1.4 偵測作業流程是否出現重工 ..................................................... 55 4.2 實例應用...................................................................... 59 4.2.1 文本分析 ................................................................... 59 4.2.2 圖形化及模型的表達方式 ....................................................... 63 4.2.3 案例數值分析 ................................................................ 64 Chapter 5 結論與未來研究方向 ...................................................... 68 5.1 結論.......................................................................... 68 5.2 未來研究方向................................................................... 69 Chapter 6 參考文獻 ............................................................... 71
dc.language.isozh-TW
dc.subject限制滿足zh_TW
dc.subject標準作業流程zh_TW
dc.subject順應性zh_TW
dc.subject流程檢驗zh_TW
dc.subject文本分析zh_TW
dc.subjectprocess inspectionen
dc.subjectconstraint satisfactionen
dc.subjectstandard operating proceduresen
dc.subjectcomplianceen
dc.subjecttext analysisen
dc.title實體標準作業流程順應性分析—限制滿足模型zh_TW
dc.titleCompliance Monitoring of Standard Operating Procedures– a Constraint Satisfaction Modelen
dc.date.schoolyear109-2
dc.description.degree碩士
dc.contributor.oralexamcommittee楊烽正(Hsin-Tsai Liu),紀佳芬(Chih-Yang Tseng)
dc.subject.keyword標準作業流程,順應性,流程檢驗,文本分析,限制滿足,zh_TW
dc.subject.keywordstandard operating procedures,compliance,process inspection,text analysis,constraint satisfaction,en
dc.relation.page74
dc.identifier.doi10.6342/NTU202101624
dc.rights.note同意授權(全球公開)
dc.date.accepted2021-07-22
dc.contributor.author-college工學院zh_TW
dc.contributor.author-dept工業工程學研究所zh_TW
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