博碩士論文 111456021 詳細資訊




以作者查詢圖書館館藏 以作者查詢臺灣博碩士 以作者查詢全國書目 勘誤回報 、線上人數:82 、訪客IP:3.147.86.216
姓名 謝瑜恬(Yu-Tien Hsieh)  查詢紙本館藏   畢業系所 工業管理研究所在職專班
論文名稱 智慧工廠舉措以實現淨零 -以紡織加工業 F 公司為例
(The Measures of Smart Factory Practices on Net Zero Emissions: Case Study of Company F in the Textile Industry)
相關論文
★ 應用灰色理論於有機農產品之經營管理— 需求預測及關鍵成功因素探討★ NAND型Flash價格與交運量預測在風險分析下之決策模式
★ 工業電腦用無鉛晶片組最適存貨政策之研究-以A公司為例★ 砷化鎵代工廠磊晶之最適存貨管理-以W公司為例
★ 資訊分享&決策制定下產銷協同關係之研究 -以IC設計業為例★ 應用分析層級法於電子化學品業委外供應商評選準則之研究
★ 應用資料探勘於汽車售服零件庫存滯銷因素分析-以C公司為例★ 多目標規劃最佳六標準差水準: 以薄膜電晶體液晶顯示器C公司製造流程為例
★ 以資料探勘技術進行消費者返廠定期保養之實證研究★ 以價值鏈觀點探討品牌公司關鍵組織流程之取決-以S公司為例
★ 應用產銷協同規劃之流程改善於化纖產業-現況改善與效益分析★ 權力模式與合作關係對於報價策略之影響研究—以半導體產業A公司為例
★ 應用資料探勘於汽車製造業之庫存原因分析★ 以類神經網路預測代工費報價---以中小面板產業C公司為例
★ 電路板產業存貨改善研究-以N公司為例★ 運用六標準差改善機台備用零件(Spare parts)存貨管理
檔案 [Endnote RIS 格式]    [Bibtex 格式]    [相關文章]   [文章引用]   [完整記錄]   [館藏目錄]   至系統瀏覽論文 ( 永不開放)
摘要(中) 紡織業是一個高耗能及高汙染的行業,其中染整製程更是整個織物生產鏈最嚴重的一環,本研究提出一智慧工廠架構應用於紡織業F公司,以該公司精縮練水洗製程為例來實踐工廠智慧化與淨零,結果顯示出顯著的環境和經濟效益。智慧化的監控管理系統和自動化控制技術通過即時數據監控和優化,精確控制藥液的使用量和溫度設定,從而減少能源和水資源的浪費,降低廢水的排放,使製程中的能源消耗顯著降低,同時減少了藥液的使用和排放量,大幅的減少了碳排放。此外,本研究大幅提升了製程的生產效率和經濟效益,由自動化設備和智慧化的監控管理系統替代了傳統手工作業,降低了人力成本,並提高了生產速度和良率,節省材料和重新加工的成本。因此,實現智慧工廠落地於紡織業,不僅提高了企業的經濟效益,還推動了行業的永續發展,符合全球環保和資源節約的需求。未來,隨著技術的進一步創新和應用深化,智慧工廠將引領紡織業邁向更加綠色、高效和靈活的未來。
摘要(英) The textile industry is characterized by high energy consumption and significant pollution. The dyeing and finishing processes represent the most critical and environmental challenges stage within the fabric production chain. This study proposes a smart factory architecture applied to Company F in the textile industry, and this study is focus in implementing intelligent solutions in washing and scouring processes. The results demonstrate substantial environmental and economic benefits. The intelligent monitoring and control management systems, combined with automation technologies, leverage real-time data monitoring and optimization to precisely control the usage of chemical solutions and temperature settings. This approach significantly reduces wastes of energy and water resource, and lowers the emissions of wastewater and exhaust. Consequently, the energy consumption of the process is markedly decreased, and the usage and discharge of chemicals are substantially decrease, leading to a significant reduction in carbon emissions.
Meanwhile, the study significantly enhances process efficiency and economic performance. The transition from traditional manual operations to automation and intelligent monitoring systems reduces labor costs, increases production capacity and quality, thereby saving material costs and reducing the need for rework. The implementation of a smart factory in the textile industry not only boosts the economic benefits for companies but also promotes sustainable development, aligning with goals of global environmental protection and resource conservation. Looking ahead, as technological innovations continually development and deeply applications, smart factories are poised to lead the textile industry towards a more sustainable, efficient, and adaptable future.
關鍵字(中) ★ 智慧工廠
★ 紡織加工業
關鍵字(英) ★ Smart Factory
★ Textile Industry
論文目次 摘要 i
Abstract ii
致謝 iii
目錄 iv
第一章 緒論 1
1.1研究背景與動機 1
1.2研究目的 3
1.3研究架構 4
第二章 文獻探討 6
2.1 智慧工廠 6
2.2 淨零排放 9
第三章 研究方法 14
3.1 管理系統架構 14
3.2 作業流程設計-以精練水洗製程為例 15
3.2.1 智慧精練水洗製程 16
3.2.2 品質檢測 21
3.3.3 AI演算 23
第四章 研究結果與討論 26
4.1 環境績效 27
4.2 經濟績效 29
4.2.1 製程設備稼動率 29
4.2.2 良率 30
4.2.3 產能 31
4.2.4 生產成本 31
4.3 其他績效 31
4.3.1智慧監測戰情中心 31
4.3.2對員工的影響 34
第五章 結論 35
英文文獻 37
參考文獻 [1] Ball, A., Craig, R., 2010, “Using Neo-institutionalism to Advance Social and Environmental Accounting,” Critical Perspectives on Accounting, Vol. 21, pp. 283-293.
[2] Bansal, P., Roth, K., 2000, “Why Companies Go Green: A Model of Ecological Responsiveness,” The Academy of Management Journal, Vol. 43, pp. 717-736.
[3] Basiri,Z. ,Heydari, J., 2017, “A Mathematical Model for Green Supply Chain Coordination with Substitutable Products,” Journal of Cleaner Production, Vol. 145, pp. 232-249.
[4] Berret, T., Slack, T., 1999, “A Framework for the Analysis of Strategic Approaches Employed by Non-profit Sport Organisations in Seeking Corporate Sponsorship,” Sport Management Review, Vol. 4, pp. 21-45.
[5] Berry, M.A., Rondinelli, D.A.,1998, “Proactive Corporate Environmental Management: A New Industrial Revolution,” The Academy of Management Executive Vol. 12, pp. 38-50.
[6] Bodansky, D., 2016, “The Paris Climate Change Agreement: A New Hope?” American Journal of International Law, Vol. 110, No. 2, pp. 288-319.
[7] Bowen, F. E., Cousins, P. D., Lamming, R. C., Faruk, A. C., 2002, “Horses for Courses: Explaining the Gap Between the Theory and Practice of Green Supply,” Greener Management International, Vol. 35, pp. 41-60
[8] Bruckner, T., Bashmakov, I. A., Mulugetta, Y., Chum, H., de la Vega Navarro, A., Edmonds, J., ... & Zhang, X., 2014, “Energy Systems,” In *Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change*.
[9] Bui, M., Adjiman, C. S., Bardow, A., Anthony, E. J., Boston, A., Brown, S., ... & Mac Dowell, N., 2018, “Carbon Capture and Storage (CCS): The Way Forward,” Energy & Environmental Science, Vol. 11, No. 5, pp. 1062-1176.
[10] Bulkeley, W. M., 2007, “IBM to Launch Push for Green-New Business to Address Cutting Energy Thirst of Computer Centers,” The Wall Street Journal, Vol. 10, pp. B4.
[11] Chen, Y., Zhang, S., Zhao, X., & Chen, W., 2018, “Smart Factory of Industry 4.0: Key Technologies, Application Case, and Challenges,” IEEE Access, Vol. 6, pp. 6505-6519.
[12] Darnall, N., Jolley, G.J., Handfiel, R., 2008, ” Environmental Management Systems and Green Supply Chain Management: Complements for Sustainability?,” Business Strategy and the Environment, Vol. 18, pp30-45.
[13] Day, G., 1994, “The Capabilities of Market-Driven Organizations,” Journal of Marketing, Vol. 58, pp. 37-52.
[14] DiMaggio, P. J., & Powell, W. W., 1983, “The Iron Cage Revisited: Institutional Isomorphism and Collective Rationality in Organizational Fields,” American Sociological Review, Vol. 48, pp. 147-160.
[15] Dowell, G., Hart, S., & Yeung, B., 2000. “Do Corporate Global Environmental Standards Create or Destroy Market Value?,” Management Science, Vol. 46, pp. 1059-1074.
[16] Fankhauser, S., Gennaioli, C., & Collins, M., 2015, “Do International Factors Influence the Passage of Climate Change Legislation?” Climate Policy, Vol. 16, No. 3, pp. 318-331.
[17] Gielen, D., Boshell, F., Saygin, D., Bazilian, M. D., Wagner, N., & Gorini, R., 2019, “The Role of Renewable Energy in the Global Energy Transformation,” Energy Strategy Reviews, Vol. 24, pp. 38-50.
[18] Hansen, J., Kharecha, P., Sato, M., Masson-Delmotte, V., Ackerman, F., Beerling, D. J., ... & Zachos, J. C., 2013, “Assessing ′Dangerous Climate Change′: Required Reduction of Carbon Emissions to Protect Young People, Future Generations and Nature,” PLOS ONE, Vol. 8, No. 12, pp. e81648.
[19] Hart, S. L., 1995,.”A Natural-Resource-Based View of the Firm,” The Academy of Management Review, Vol. 20, pp. 986-1014.
[20] Hepburn, C., Adlen, E., Beddington, J., Carter, E. A., Fuss, S., Mac Dowell, N., ... & Williams, C. K., 2019, “The Technological and Economic Prospects for CO2 Utilization and Removal,” Nature, Vol. 575, No. 7781, pp. 87-97.
[21] Hsu, C. W., Hu, A. H., 2011, “Applying Hazardous Substance Management to Supplier Selection Using Analytic Network Process,” Journal of Cleaner Production, Vol. 17, pp. 255-264.
[22] International Energy Agency (IEA), 2020, “Global EV Outlook 2020: Entering the Decade of Electric Drive?”
[23] International Energy Agency (IEA), 2021, “Energy Efficiency 2021.”
[24] International Renewable Energy Agency (IRENA), 2020, “Global Renewables Outlook: Energy Transformation 2050.”
[25] IPCC, 2014, “Carbon Dioxide Capture and Storage,” In *Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change*.
[26] Ivanov, D., Tsipoulanidis, A., & Schönberger, J., 2016, “Global Supply Chain and Operations Management: A Decision-Oriented Introduction to the Creation of Value”, Springer.
[27] J. S. R. Jang, “ANFIS: Adaptive-Network-based fuzzy inference systems,” IEEE Transaction on Systems, Man, and Cybernetics, vol. 23, pp. 665-685, May 1993.
[28] Jordan, M. I., & Mitchell, T. M. , 2015, “Machine learning: Trends, perspectives, and prospects. Science,” 349(6245), 255-260. • Kagermann, H., Wahlster, W., & Helbig, J. (2013). Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0. acatech–National Academy of Science and Engineering.
[29] Kagermann, H., Wahlster, W., & Helbig, J., 2013, “Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0,” Final Report of the Industrie 4.0 Working Group.
[30] Lamming, R., Hampson, J., 1996, “The Environment as a Supply Chain Management Issue,” British Journal of Management, Vol. 7, pp. 45-62.
[31] Lee, I., & Lee, K., 2015, “The Internet of Things (IoT): Applications, investments, and challenges for enterprises,” Business Horizons, Vol. 58, No. 4, pp. 431-440.
[32] Lee, J., Bagheri, B., & Kao, H. A. (2015). A Cyber-Physical Systems Architecture for Industry 4.0-based Manufacturing Systems. Manufacturing Letters, 3, 18-23. • Lee, J., Davari, H., Singh, J., & Pandhare, V. (2018). Industrial Artificial Intelligence for Industry 4.0-based Manufacturing Systems. Manufacturing Letters, 18, 20-23.
[33] Lee, J., Kao, H. A., & Yang, S., 2020, “Service innovation and smart analytics for Industry 4.0 and big data environment,” Procedia CIRP, Vol. 16, pp. 3-8.
[34] Li, L., He, Y., & Zhang, D., 2017, “Multiple Views of Smart Manufacturing Systems in the Context of Industry 4.0,” IFAC-PapersOnLine, Vol. 50, No. 1, pp. 4015-4020.
[35] Lin, Y.J., Wei, S.H., Huang, C. Y., 2019, “Intelligent Manufacturing Control System: The Core of Smart Factory,” 25th International Conference on Production Research Manufacturing Innovation: Cyber Physical Manufacturing.
[36] Lorenzoni, I., Nicholson-Cole, S., & Whitmarsh, L., 2007, “Barriers Perceived to Engaging with Climate Change among the UK Public and Their Policy Implications,” Global Environmental Change, Vol. 17, No. 3-4, pp. 445-459.
[37] Lu, Y., Xu, X., Wang, L., & Xie, S., 2020, “Smart Manufacturing Process and System Automation – A Critical Review of the Standards and Enabling Technologies,” Automation in Construction, Vol. 107, pp. 102142.
[38] McCollum, D. L., Echeverri, L. G., Busch, S., Pachauri, S., Parkinson, S., Rogelj, J., ... & Riahi, K., 2018, “Connecting the Sustainable Development Goals by Their Energy Inter-Linkages,” Environmental Research Letters, Vol. 13, No. 3, pp. 033006.
[39] McKinsey & Company, 2020, “Climate Risk and Response: Physical Hazards and Socioeconomic Impacts.”
[40] Negri, E., Fumagalli, L., & Macchi, M., 2017, “A Review of the Roles of Digital Twin in CPS-based Production Systems,” Procedia Manufacturing, Vol. 11, pp. 939-948.
[41] Nordhaus, W., 2019, “Climate Change: The Ultimate Challenge for Economics,” American Economic Review, Vol. 109, No. 6, pp. 1991-2014.
[42] OECD, 2017, “Investing in Climate, Investing in Growth,” OECD Publishing.
[43] Pacala, S., & Socolow, R., 2004, “Stabilization Wedges: Solving the Climate Problem for the Next 50 Years with Current Technologies,” Science, Vol. 305, pp. 968-972.
[44] Porter, M. E., 1980, “Competitive Strategy: Techniques for Analyzing Industries and Competitors,” New York: Free Press.
[45] Porter, M. E., Linde, C.V.D., 1995, “Green and Competitive: Ending the Stalemate,” Harvard Business Review, Vol. 73, pp. 120-134.
[46] Qi, Q., & Tao, F., 2018, “Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison,” IEEE Access, Vol. 6, pp. 3585-3593.
[47] Roberts, S., & Thumim, J., 2006, “A Framework for Assessing the Distribution of Benefits from Environmental Policy,” Environmental Economics and Policy Studies, Vol. 7, No. 4, pp. 319-341.
[48] Rogelj, J., Shindell, D., Jiang, K., Fifita, S., Forster, P., Ginzburg, V., ... & Matthews, J. B. R., 2018, “Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development,” In Global Warming of 1.5°C: An IPCC Special Report.
[49] Sarkis, J., Sroufe, R., 2004, “Strategic Sustainability: The State of the Art In Corporate Environmental Management Systems: Introduction,” Greener Management International, Vol. 46, pp. 5-11.
[50] Slater, S. F., Narver, J. C., 1998, “Research Notes and Communications. Full Access. Customer-led And Market-oriented: Let′s Not Confuse The Two,” Strategic Management Journal, Vol. 19, pp. 1001-1006.
[51] Stern, N., 2006, “The Stern Review on the Economics of Climate Change,” American Economic Review, Vol. 98, No. 2, pp. 1-37.
[52] Tao, F., Zhang, M., Liu, Y., & Nee, A. Y. C., 2019, “Digital Twin in Industry: State-of-the-Art,” IEEE Transactions on Industrial Informatics, Vol. 15, No. 4, pp. 2405-2415.
[53] Tian, Y., Wang, S., & Zuo, M., 2020, “Study on the Integration of Machine Learning and Artificial Intelligence for Improving Product Quality Control in Industry 4.0,” IEEE Access, Vol. 8, pp. 5253-5264.
[54] Victor, D. G., Akimoto, K., Kaya, Y., Yamaguchi, M., Cullenward, D., & Hepburn, C., 2014, “Prove Paris Was More than Paper Promises,” Nature, Vol. 548, No. 7666, pp. 25-27.
[55] Walton, S. V., Handfield, R. B., Melnyk, S. A., 1998, “The Green Supply Chain: Integrating Suppliers into Environmental Management Processes,” International Journal of Purchasing and Materials Management, Vol. 34, pp. 2-11.
[56] Wan, J., Tang, S., Li, D., Wang, S., Liu, C., Abbas, H., & Vasilakos, A. V., 2016, “A Manufacturing Big Data Solution for Active Preventive Maintenance,” IEEE Transactions on Industrial Informatics, Vol. 13, No. 4, pp. 2039-2047.
[57] Wang, S., Wan, J., Zhang, D., Li, D., & Zhang, C., 2016, “Towards smart factory for industry 4.0: A self-organized multi-agent system with big data based feedback and coordination,” Computer Networks, Vol. 101, pp. 158-168.
[58] Whitmarsh, L., Seyfang, G., & O′Neill, S., 2011, “Public Engagement with Carbon and Climate Change: To What Extent is the Public ‘Carbon Capable’?” Global Environmental Change, Vol. 21, No. 1, pp. 56-65.
[59] Xu, L. D., Xu, E. L., & Li, L., 2018, “Industry 4.0: State of the art and future trends,” International Journal of Production Research, Vol. 56, No. 8, pp. 2941-2962.
[60] Zhang, Y., He, X., & Tang, J., 2019, “Research on Human-Computer Interaction and Machine Learning Techniques in the Smart Factory,” Journal of Ambient Intelligence and Humanized Computing, Vol. 10, No. 5, pp. 1807-1816.
[61] Zhong, R. Y., Xu, X., Klotz, E., & Newman, S. T., 2017, “Intelligent Manufacturing in the Context of Industry 4.0: A Review,” Engineering, Vol. 3, No. 5, pp. 616-630.
[62] Zhou, M., Pan, Y. C., Chen, Z. M., Yang, W., Li, E. R., 2012, “Selection and Evaluation of Green Production Strategies: Analytic and Simulation Models,” Journal of Cleaner Production, Vol. 26, pp. 9-17.
指導教授 陳振明(Jen-Ming Chen) 審核日期 2024-7-22
推文 facebook   plurk   twitter   funp   google   live   udn   HD   myshare   reddit   netvibes   friend   youpush   delicious   baidu   
網路書籤 Google bookmarks   del.icio.us   hemidemi   myshare   

若有論文相關問題,請聯絡國立中央大學圖書館推廣服務組 TEL:(03)422-7151轉57407,或E-mail聯絡  - 隱私權政策聲明