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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/117641


    Title: 自動化流程機器人與人工智慧發展之探討
    The Research of Robotic Process Automation Optimization and Artificial Intelligence Development
    Authors: 李龍憲
    Lee, Lung Hsien
    Contributors: 季延平
    李龍憲
    Lee, Lung Hsien
    Keywords: 自動化流程機器人
    人工智慧
    工業4.0
    物聯網
    大數據
    企業流程優化
    Date: 2018
    Issue Date: 2018-06-12 17:26:36 (UTC+8)
    Abstract: 2017年英國《經濟學人》雜誌曾提出，「世界上最寶貴的資源不再是石油，而是數據」。隨著物聯網時代來臨，工業應用領域也開始整合各種技術而掀起新一波工業革命。因為大量自動化及數據化，除了升級自動化設備、整合網通系統，監控設備產生的大數據，透過工業電腦進行分析，經由人工智能判斷邏輯產生條件，再由設備自主處理各種生產問題。除去大量勞動，專注於大數據自動化處理，即能生產更優質的產品，並且優化流程，降低企業成本。
    自動化流程機器人(Robotic Process Automation)能自動的管理並執行企業大量耗費時間與人力的業務流程，可用於客戶服務、人力管理、供應鏈管理、採購、會計等範疇。物聯網(IoT)時代下的機器人自動化流程加入了認知運算等新興技術，更能進一步提升企業效率並降低成本。自動化流程機器人(Robotic Process Automation)儼然成下一個新的生產力革命。
    市場研究機構IDC預測，2017年全球在認知和人工智慧系統支出將達到125億美元，和2016年相比成長達59.3%。Google母公司Alphabet公開測試無人駕駛汽車、阿里宣佈投資千億成立達摩院、百度機器人入駐肯德基等等。人工智慧(Artificial Intelligence)將顛覆商業思維、改寫商業模式。在2020年，人工智慧(Artificial Intelligence)將成為市場上真正的「主流」技術思維。IDC並且認為亞洲將在2020年成為全球第二大認知與人工智慧輸出區域。
    本文探討自動化流程機器人與人工智慧之間的關聯，以及流程優化後對企業所產生的影響與變革．並且針對個案的自動化解決方案所達到的效益與後續發展進行評估與檢討，藉以提升自動化解決方案，協助企業在未來挑戰的競爭環境中創造最佳化優勢．
    “The Economist” stated in 2017 that “the world’s most precious resource is no longer oil but data”. With the advent of the Internet of Things, industrial applications have begun to integrate various technologies and set off a new wave of industrial revolution. Because of a large amount of automation and data, in addition to upgrading automation soluitons, integrating netcom systems, and monitoring the big data generated by the solutions, analysis is performed through industrial computers, and conditions are generated through the logic judgment of artificial intelligence, and then the solutions autonomously handles various processes. It can produce better products, optimize the process and reduce business costs to focus on automation of big data and to save a lot of labor hiring.
    Robotic Process Automation can automate the management and execution of a large number of business processes that consume time and manpower, and can be used in areas such as customer service, manpower management, supply chain management, procurement, finance and accounting. The robotic automation process in the Internet of Things (IoT) era has added emerging technologies such as cognitive computing to further enhance the efficiency of enterprises and to reduce costs. Robotic Process Automation becomes the next new productivity revolution.
    In 2017, marketing research firm, IDC, predicts that global spendings on cognitive and artificial intelligence systems will reach US$12.5 billion, which represents a growth of 59.3% compared to 2016. Google, the parent company of Alphabet, publicly tests driverless cars, Ali announced that it has invested 100 billion to establish Daruma House, Baidu Robots has settled in Kentucky. Artificial Intelligence will disrupt business thinking and rewrite business models. In 2020, Artificial Intelligence will become the real "mainstream" technical thinking in the market. IDC also believes that Asia will become the world’s second largest cognitive and artificial intelligence output region in 2020.
    The article discusses the relationships between robotic process automation and artificial intelligence, and also the impact and changes after implementing the solutions. It has also evaluated and reviewed the effectiveness and following development of the automated solutions, so as to enhance the values of automation solutions and to help companies create optimal advantages in the future challenging and competitive environment.
    Reference: 1. 余至浩，https://www.pwc.tw/zh/news/media/media-20171218-4.html，2017年。
    2. 李開復，人工智慧來了，天下文化，2017年7月12日。
    3. 吳凱琳，AI來襲！8億個工作消失，但有9億個工作崛起天下雜誌，2017年。
    4. 林軒田，What’s next? 2018年AI趨勢大預測，數位時代，2017年。
    5. 林昱均，企業福音？自動化流程機器人機器人將減少25％會計與人力成本，ETtoday，2018年。
    6. 宋晁宇，企業如何善用大數據來提升經營績效，管理知識中心，2017年。
    7. 徐瑞廷，讓員工從瑣事中鬆綁！2個自動化技術，幫企業省成本、帶效益，Manager Today，2018年。
    8. 翁書婷，AI定義新時代-當人類的眼睛、耳朵，不再是唯一可思考和探索世界的工具，2017年。
    9. 翁書婷，人工智慧夯詞彙-卷積神經網路、雞尾酒會效應、ImageNet、1：N，2017年。
    10. 程琪。中國AI技術爆發！2張圖看：食衣住行育樂全面智慧化...美國將失領導地
    位？台科大數據研究中心，2018。
    11. 陳永晁，軟體流程改善專案導入效益探討-以個案公司為例，東海大學管理
    碩士在職專班，碩士論文，2009年。
    12. 陳智德，機器人自動化流程加入認知運算協助企業降低成本，Digitimes，2017年。
    13. 陳復霞，野村研究所以機器人執行交易後作業流程CTIMES/SmartAuto, 2017。
    14. 張小玫，未來 AI 發展八大新趨勢，科技政策研究與資訊中心，2017年。
    15. 張道宜，覺得工作無聊?小心機器人取代你，Cheers，2017年。
    16. 黃齊元，AI衝擊來了》勞力被取代、人資卻變熱門，為什麼？，商業週刊，2018。
    17. 曾韵韵，AI基因在地化產業進化關鍵，經濟日報，2018年。
    18. 曾筱媛，正面迎擊人機合作的時代：AI時代3大關鍵人才，數位時代，2017
    年。
    19. 鄭興、劉禮賢，智慧未來：RPA (Robotic Process Automation)自動化流程機器人， https://www2.deloitte.com/tw/tc/pages/operations/articles/robotic-process-automation.ht ml，2017年。
    20. 羅仁權，機器人自動化與智慧工廠的挑戰與商機，物聯網，2014年。
    21. 羅耀宗譯，四步驟落實人工智慧，哈佛商業評論，2018年。
    22. 科技政策研究與資訊中心，2030年人工智慧將提高全球GDP達15.7兆美元，2017
    年。
    23. 科技政策研究與資訊中心，人工智慧對企業來說，機器人自動化流程機器人趨重要，
    http://iknow.stpi.narl.org.tw/Post/Read.aspx?PostID=13993，2017年。
    24. 科技政策研究與資訊中心，自動化的五項陷阱，2017年。
    25. 麥肯錫，智能流程自動化將成下一代運營模式核心引擎，投資回報率超300%，2017
    年。
    26. 智庫百科，流程優化，2017年。
    27. 掃文資訊，RPA的發展， 2018年。
    28. 國脈物聯網，德勤：人工智慧與商業應用，2017年。
    29. 勤業眾信，人工智慧商業價值勢不可擋AI發展的現在與未來，2017 年。
    30. 雷鋒網，從馬文·閔斯基到 AlphaGo，人工智慧走過了怎樣的 70 年？2016年。
    31. 數位時代，11個趨勢預測：人工智慧將會如何影響人類的職業?，2018年。
    32. 蕭佑和，完整解析AI人工智慧：3大浪潮＋3大技術＋3大應用大和有話說，2018
    年。
    33. 鷹騰諮詢，上市·策，2008年199IT互聯網數據中心，人工智慧與商業應用研究報
    告，2017年。
    34. e-works製造業信息化門戶網，企業流程優化的三重境界，2016年。
    35. Hsinlan Chen，什麼是人工智慧（Artificial Intelligence）?，INSIDE，2016年。
    36. PwC，2017年全球金融科技調查台灣概要，2017年。
    37. TechNews，Gartner：到了2020年，人工智慧創造的工作機會將超過其取代的數量，
    2017年。
    1. A. Abbattista, M. Soderberg, T. Morganti, J. Hejtmanek, Automate this-A guide to robotic process automation, Deloitte, 2018.
    2. A. A. Ramos, How to prep your enterprise for the AI Revolution, Process Excellence Network, 2018.
    3. A. Burgess, Artificial intelligence and robotics: Separating reality from the hype, sourcingfocus.com, 2016.
    4. A. Burgess, Robotic Process Automation & Artificial Intelligence, Disruption, 2017.
    5. A. Burgess, RPA and AI – the same but different, Symphony, 2015.
    6. A. Burgess, The Executive Guide to Artificial Intelligence-How to Identify and Implement Applications for AI in Your Organization, Palgrave Macmillan, 2018.
    7. Accenture, Robotics Process Automation in Banking, Insurance & Capital Markets, 2018.
    8. Accenture, Technology Vision, 2018.
    9. Appian, RPA and Enterprise Automation: Technologies and Strategies to Win in the Digital Economy, 2018.
    10. Aitrends, RPA is Harnessing AI to Automate IT Tasks and Business Processes, 2018.
    11. A. Tammina, S. Lyer, RPA Balanced Scorecard-Taking intelligent automation to the next level, EdgeVerve, 2017.
    12. BCG Analysis, BCG: Powering The Service Economy w/ RPA, 2017.
    13. B. V. D. Mark, The difference between Robotic Process Automation and Artificial Intelligence, Linkedin, 2016.
    14. C. Boulton, What is RPA? A revolution in business process automation, CIO, 2018.
    15. C. L. Clair, The Forrester Wave™: Robotic Process Automation, Forrester, 2017.
    16. C. Nicholson, What is the difference between AI and RPA?, Quora, 2018.
    17. C. Tornbohm, R. Dunie, Market Guide for Robotic Process Automation Software, Gartner, 2017.
    18. CXO today.com, AI To Bring More Jobs, Revenues to Businesses, 2017.DL4J, Robotic Process Automation (RPA), AI and Machine Learning, 2018.
    19. Digital Workforce, RPA vs. Integration, 2017.
    20. D. Moss, Product and Potential, blueprism, 2017.
    21. D. Schatsky, C. Muraskin, R. Gurumurthy, Cognitive technologies: The real opportunities for business, Deloitte University Press, January 26, 2015, https://dupress.deloitte.com/dup-us-en/deloitte-review/issue-16/
    cognitive-technologies-business-applications.html.
    22. E. Quirk, Artificial Intelligence Umbrella Glossary: Machine Learning, AI, RPA & More, Solutions Review, 2018.
    23. Everest Group, Making RPA Enterprise-Grade at Scale, 2017.
    24. EY, Robotic process automation White paper, 2015.
    25. First Post, Artificial Intelligence cos` revenue to hit $3 bn by 2024, says report; Deep Learning to have fastest growth, 2017.
    26. Grand View Research, Robotic Process Automation Market Size, Share & Trends Analysis Report By Services (Professional Services, Training Services), By Organization, By Application, By Region, And Segment Forecasts, 2018-2024.
    27. Harvard Business Review, “How AI Will Change the Way We Make Decisions,” July 26, 2017, https://hbr.org/2017/07/how-ai-will-change-the-waywe-make-decisions.
    28. I. Hawkins, RPA and Cognitive Automation: only for big business?, PEX, 2018.
    29. Intelligent Sourcing, Better Together: AI & RPA in Content-Centric Business Processes, 2018.
    30. IRPA, Introduction to Robotic Process Automation, 2015.
    31. J. P. Makkonen, The tools of the future today - What is robotic process automation, artificial intelligence and machine learning?, Valamis.com, 2017.
    32. K. Ko, V. Tsang, Automation for actuarial processes-Robotic, EY, 2016.
    33. MarketsandMarkets, Artificial Intelligence Market worth 190.61 Billion USD by 2025, 2016.
    34. McKinsey, An executive’s guide to AI, 2018.
    35. McKinsey, Artificial Intelligence: The Next Digital Frontier, 2017.
    36. NewGenApps, Know the Difference between Artificial Intelligence and RPA, 2018.
    37. Oracle, A New Shared Vision, 2018.
    38. P. Fersht, Gartner: 96% of customers are getting real value from RPA? Really?, Horses for Resources, 2017.
    39. P. Khurana, Moving From RPA To AI: Are You Prepared For It?, Grid Infocom, 2018.
    40. P. Robledo, BPM 2018: Top 10 BPM Industry Trends This Year, PEX, 2018
    41. R. Jesuthasan & J. Boudreau, Thinking Through How Automation Will Affect Your Workforce, Harvard Business Review, 2017.
    42. R. Ronanki, Artificial Intelligence for the Real World, Deloitte, 2017.
    43. S.Overby, 11 ways to address RPA and AI in IT outsourcing contracts, CIO, 2017.
    44. Tanna Partners, RPA and AI Salary Guide, 2018.
    45. T. H. Davenport, J. Kirby, Only Humans Need Apply: Winners and Losers in the Age of Smart Machines, Harper Business, 2016.
    46. TMT Predictions 2016: Cognitive technologies enhance enterprise software, https://www2.deloitte.com/global/en/pages/technology-media-andtelecommunications/articles/tmt-pred16-tech-cognitive-technologies-enterprise-software.html.
    47. T. Petäjämaa, Adding Value With RPA, Siili Solutions, 2017.
    48. Tractica, RPA & Artificial Intelligence for Banking, Financial Services & Insurance, 2017.
    49. Uipath, RPA ( Robotic Process Automation ), 2018.
    50. WNS, RPA & AI in Insurance: Road to Adoption, 2018.
    51. WorkFusion, 9 AI trends to look for in 2018 RPA 2.0 initiatives, 2017.
    52. ZDNet, More artificial intelligence, fewer screens: the future of computing unfolds, 2017.
    Description: 碩士
    國立政治大學
    經營管理碩士學程(EMBA)
    101932119
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0101932119
    Data Type: thesis
    Appears in Collections:[經營管理碩士學程EMBA] 學位論文

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