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    Title: 邁向工業4.0之紡織產業供應鏈管理: 以A公司為例
    Supply chain management of textile industry towards Industry 4.0:a case study of A company
    Authors: 王心華
    Wong, Sin-Fah
    Contributors: 羅明琇
    Lo, Ming-Shiow
    王心華
    Wong, Sin-Fah
    Keywords: 工業4.0
    供應鏈管理
    供應鏈作業參考模型
    Industry 4.0
    Supply Chain Management
    Supply-Chain Operations Reference Model
    Date: 2019
    Issue Date: 2019-08-07 17:10:16 (UTC+8)
    Abstract: 工業4.0此名詞於2011年德國漢諾威工業博覽會被首次討論,2012年底由Bosch為首的推動小組向德國政府提出發展建言,並在 2013年4月正式對外發表。工業4.0是指結合虛擬網絡-實體物理系統、大數據、物聯網、人工智慧、智慧工廠、雲端運算等技術,達到降低生產成本及提高生產效率和品質,使整條供應鏈可以更具彈性及迅速反應市場需求。

    科技和網路的進步促使製程逐步自動化,讓製造業的生產模式往更精密的客制化系統發展,以在激烈競爭中取得優勢。以往企業都是透過大量生產達到規模經濟以降低生產成本,但客制化的情況下,企業無法達到規模經濟而造成成本難以降低,而工業4.0能解決大量生產的成本及客制化的矛盾。可見不久的將來,生產模式將會以客制化智慧製造為主要趨勢。

    本研究採取質性研究之深度訪談方式進行資料蒐集,選紡織A公司為個案研究對象,並透過供應鏈作業參考模型(Supply-Chain Operations Reference model,簡稱SCOR模型)作為論文的研究架構,SCOR模型將分為五大流程:規劃、採購、製造、配送、退貨,而SCOR模型適用於不同產業及領域,因此會以這流程去探討導入工業4.0對紡織A公司供應鏈所帶來的效益及改善,並發現A公司在邁向工業4.0後,在製造流程中改善程度最高;可靠度、回應能力、敏捷度、成本、資產管理上均獲得改善,其他流程則部分改善,效益無製造大,總體提升了A公司的競爭力。台灣是製造業重點發展經濟的國家,若企業無法及時改變並趕上工業4.0的浪潮,恐將失去過往的優勢,因此在工業4.0下的供應鏈管理也顯得極為重要。
    The term, Industry 4.0, was first discussed at the Germany Hannover Fair in 2011. The definition of Industry 4.0 is the mode of integration of Cyber-Physical System, Big Data, Internet of Things, Smart factory, Cloud computing and other technologies, to reduce cost or improve efficiency and quality of production so that supply chain could become more flexible and rapid to respond the demand of market.

    Due to the improvement of technology and Internet, manufacturing processes in manufacturing industry gradually become automatic which leads to production mode turning to more sophisticated customized system, and then the company could get the dominant position in competitive market. In the past, companies usually pursued mass production to reduce cost through economies of scale. However, in the situation of customized production, it is hard for companies to reach economies of scale. Now, the dilemma between lower cost by mass production and customization can be solved under Industry 4.0. It can be foreseen that smart customized manufacturing will be main trend soon.

    This research adopt the in-depth interview method of qualitative research to collect data, selected textile industry A company as a case study object, and utilizes Supply-Chain Operations Reference model (SCOR model) as research structure. There are five process in SCOR model: Plan, Source, Make, Deliver, Return, and it is suitable for different kinds of industries. So the research tries to find out the effect of introducing Industry 4.0 into supply chain for the textile company which is investigated deeply under the process of SCOR model, after A Company towards Industry 4.0, The highest level of improvement in make processes was achieved, with improvements in reliability, responsiveness, agility, cost, and asset management, while other processes were partially improved, and overall enhanced the competitiveness of Company A. Taiwan is a manufacturing industry focused on the development of the economy, if enterprises cannot change in time and catch up with the wave of Industry 4.0, it is afraid to lose the advantages of the past, so under Industry 4.0 supply chain management is also extremely important.
    Reference: 文獻參考
    David F.Ross. (1997). Competing through supply chain management: creating market-winning strategies through supply chain partnerships. Springer Science & Business Media.
    Engelman, R. (2015). The Second Industrial Revolution. https://doi.org/10.2307/2224131
    Gandomi, A., &Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144. https://doi.org/10.1016/j.ijinfomgt.2014.10.007
    Hashem, I. A. T., Yaqoob, I., Anuar, N. B., Mokhtar, S., Gani, A., &Ullah Khan, S. (2015). The rise of “big data” on cloud computing: Review and open research issues. Information Systems, 47, 18. https://doi.org/10.1016/j.is.2014.07.006
    Henning, Kagermann. Wolfgang, Wahlster . Johannes, H. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0. Final report of the Industrie 4.0 WG. https://doi.org/10.13140/RG.2.1.1205.8966
    Hoppe, G. (2014). High-Performance Automation verbindet IT und Produktion. Springer Vieweg, Wiesbaden.
    Lee, J., Ardakani, H. D., Yang, S., &Bagheri, B. (2015). Industrial Big Data Analytics and Cyber-physical Systems for Future Maintenance & Service Innovation. Procedia CIRP, 38, 3–7. https://doi.org/10.1016/j.procir.2015.08.026
    Lee, J., Kao, H. A., &Yang, S. (2014). Service innovation and smart analytics for Industry 4.0 and big data environment. Procedia CIRP, 16, 6. https://doi.org/10.1016/j.procir.2014.02.001
    Lee, J., Wu, F., Zhao, W., Ghaffari, M., Liao, L., &Siegel, D. (2014). Prognostics and health management design for rotary machinery systems—Reviews, methodology and applications. Mechanical Systems and Signal Processing, 42(1–2), 314–334. https://doi.org/10.1016/j.ymssp.2013.06.004
    Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Byers, A. H. (2011). Big data The next frontier for innovation, competition, and productivity. Journal of Obstetrics and Gynaecology (Vol. 29). https://doi.org/10.1080/01443610903114527
    Mrugalska, B., &Wyrwicka, M. K. (2017). Towards Lean Production in Industry 4.0. Procedia Engineering, 182, 466–473. https://doi.org/10.1016/j.proeng.2017.03.135
    Supply Chain Council. (2012). Supply Chain Operations Reference Model Rev.11.0. Supply Chain Operations Management. https://doi.org/10.1108/09576059710815716
    The Economist. (2012). Special Report Manufacturing and Innovation: A third industrial revolution. The Economist, 403(8781), 1. https://doi.org/10.1049/et:20080718
    Weyer, S., Schmitt, M., Ohmer, M., &Gorecky, D. (2015). Towards industry 4.0 - Standardization as the crucial challenge for highly modular, multi-vendor production systems. IFAC-PapersOnLine, 28(3), 579–584. https://doi.org/10.1016/j.ifacol.2015.06.143
    World Trade Organization. (2017). World Trade Statistical Review 2017, 181. Retrieved from https://books.google.pt/books?id=h50nvgAACAAJ
    何川澤. (2017). 工業 4.0 應用於粉末冶金製程改善降低生產成本的策略. 育達科技大學.
    侯奕妤. (2017). 台灣紡織業經營策略分析-以 F 公司為例. 國立雲林科技大學.
    倪世傑. (2016). 置身工業4.0下的機器與勞工.
    吳佳蓉. (2012). 對外直接投資對台灣紡織業與電子業出口貿易影響之研究. 國立台北大學.
    吳政哲. (2016). 以工業 4.0 理論探討食品工廠提升產能之研究. 明道大學.
    呂函儒. (2016). 價值驅動為導向之生產力4.0推動模式建構暨個案分析. 元智大學.
    國家發展委員會. (2015). Taiwan 2020 (創意臺灣)政策白皮書.
    孫義雄. (2004). 深度訪談法與犯罪成因之探索, 221–232.
    宏遠興業股份有限公司. (2017). 宏遠興業2016企業社會責任報告書. 台南.
    廖炫富. (2010). 台灣紡織業之產業內貿易效果及其決定因子之探討-兼論參與WTO及紡品配額制取消之影響. 國立中正大學.
    張小玫. (2015). 物聯網將掀起工業革命4.0. Retrieved from https://portal.stpi.narl.org.tw/index/article/10095
    徐芳瑜. (2015). 台灣紡織業客戶對國際快遞服務滿意度之研究- 以 F 公司為例. 國立交通大學.
    李傑. (2016). 工業大數據-工業4.0時代的智慧轉型與價值創新. 台北市.
    李東岳. (2005). SCOR為基之供應鏈規劃-以多廠區生產規劃為例. 國立清華大學.
    林宏遠. (2015). 規劃智慧產線-以檢測筆記型電腦產線為例. 東海大學.
    林郁杰. (2013). 社會企業資源平台之研究-以CORPS的觀點. 國立政治大學.
    江淑美、吳伊勻、翁士勛、劉育雯. (2000). 教育研究法專題研究報告--個案研究.
    潘佳憶. (2016). 設備供應商實施工業 4.0 轉型之研究-以A公司為例. 國立政治大學.
    王怡惠. (2015, August). 從工業4.0 看我國生產力4.0之挑戰, 111–119.
    紡拓會. (2018). 2017 年臺灣紡織工業概況.
    紡紗工業同業公會. (2016, August). 以智慧生產因應 全球第四次工業革命潮流, 6.
    經濟部工業局. (2012). 產業節水與水再生技術手冊-紡織業.
    經濟部統計處. (2018). 製造業生產價值—按中行業分.
    蔡源泰. (2009). 企業財務風險與效率之研究 -以台灣上市紡織業為例. 國立高雄第一科技大學.
    行政院. (2015). 行政院生產力 4.0 發展方案.
    行政院主計總處. (2016). 行業標準分類第 10 回.
    趙山貴. (2017). 紡織業導入工業 4.0 之關鍵因素-以宏遠興業為例. 國立中正大學.
    辛石城. (2013). 衰退產業生存策略之研究-以紡織業為例. 明道大學.
    邱鈺惠. (2017). SCOR 模型研究與探討. 國立中央大學.
    陳向明. (2002). 社會科學質的研究. 台北: 五南.
    黃子嘉. (2014). 運用 SCOR模型建構太陽能電池導電漿企業供應鏈績效衡量指標. 國立交通大學.
    黃愉棻. (2018). 電子遊戲機對非洲市場行銷策略之研究:以K公司為例. 國立高雄大學.
    黃聖元. (2009). 中國-東協優惠性原產地規則對台灣紡織業出口貿易轉向影響. 國立臺灣海洋大學.
    Description: 碩士
    國立政治大學
    企業管理研究所(MBA學位學程)
    105363129
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0105363129
    Data Type: thesis
    DOI: 10.6814/NCCU201900244
    Appears in Collections:[企業管理研究所(MBA學位學程)] 學位論文

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