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| Title: | 工業4.0下製造管理議題及相關的決策資訊系統
Manufacturing Management and Related Decision Support Systems Under Industry 4.0 |
| Authors: | 林青平
Lin, Ching-Ping |
| Contributors: | 吳安妮
Wu, Anne
林青平
Lin, Ching-Ping |
| Keywords: | 工業4.0
製造管理議題
決策資訊系統
Industry 4.0
Manufacturing management
Decision support system |
| Date: | 2018/06/22 |
| Issue Date: | 2018-07-11 17:22:32 (UTC+8) |
| Abstract: | 隨著客製化需求提升，企業希望以合理之成本，提升整體反應速度及生產靈活性，保持其競爭力，故工業4.0已成為當前製造業之趨勢。工業4.0並非突然出現之產業革命，而是隨著科技進步，而逐漸成熟之概念。然而，工業4.0尚未有明確之定義，各公司導入工業4.0之目的及程度皆不同。
工業4.0之導入不僅需要龐大之資金投入，也需要與以往全然不同之組織思維。導入工業4.0將會帶來與以往完全不同之製造管理議題，產業界也希望透過新科技，如決策資訊系統，達到更快速且高品質之決策。目前之研究都只有分別針對工業4.0之特色、製造管理議題及與其相關之決策資訊系統；且目前之研究在實務方面數量有限，多侷限於理論層面。
因此，本研究將以一家個案公司導入工業4.0作為探討標的，並深入分析其所帶來之不同傳統之製造管理議題及運用管理決策資訊系統輔助之。
With the increase in customization requirements, companies hope to maintain their competitiveness by increase the speed of response and production flexibility at a reasonable cost. As a result, Industry 4.0 has become the trend in the current manufacturing industry. Industry 4.0 is not an industrial revolution that suddenly emerged, but a concept of gradual maturity as technology advances. However, Industry 4.0 has not yet been clearly defined. The purpose and degree of each company`s introduction into Industry 4.0 are different.
The introduction of Industry 4.0 not only requires huge capital investment, but also requires organizational mindset that is completely different from the past. The introduction of Industry 4.0 will bring about completely different manufacturing management issues than before. The industry also hopes to achieve faster and higher-quality decisions through new technologies such as decision supporting information systems. All the current researches have only focused on the characteristics of Industry 4.0, manufacturing management issues, and the decision support information systems. Moreover, the current research has a limited number of practices and is limited to the theoretical level.
Therefore, this study will introduce a case company as the subject of the study, and further analyze the different traditional manufacturing management issues brought by it and use the management decision support system to assist it. |
| Reference: | 中文部分
呂正華，2017，產業競爭力提升與生產力4.0，台北：國家圖書館。
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：天下雜誌。
林上育，2017，工業4.0與作業價值管理(AVM)之結合，國立政治大學會計研究所碩士論文。
研華科技，2017，智慧工廠核心靈魂在哪裡？──研華林口互聯網體驗園區，網址：https://buzzorange.com/techorange/2017/01/12/advantech-factory/，搜尋日期：2018年4月26日。
韋康博，2016，工業4.0：從製造業到「智」造業，下一波產業革命如何顛覆全世界？台北：商周出版。
許家愷，2016，工業4.0對製造業的影響分析－以元件製造商為例，淡江大學管理科學學系企業經營碩士在職專班碩士論文。
陳端武，2018，機器人是帶來巨變的顛覆性技術，網址：https://www.digitimes.com.tw/iot/article.asp?cat=158&cat1=20&cat2=90&id=0000524399_VML2Y8P6LVMERD8S99VG0，搜尋日期：2018年4月23日。
廖家宜，2018，智慧製造大趨勢：經驗傳承、資訊創新應用是關鍵，網址：https://www.digitimes.com.tw/tech/dt/most.asp?pack=12880&cnlid=1&cat=10，搜尋日期：2018年4月23日。
籃貫銘，2018，2018年台灣工業電腦的出貨總值將成長12.2%。網址：https://www.ctimes.com.tw/DispNews-tw.asp?O=HK234CT2U2KSAA00NJ，搜尋日期：2018年4月23日
經濟部統計局，2018年，當前經濟情勢概況：機械產業生產力（4月）
經濟部工業局，2016年，五大產業創新研發計畫智慧機械產業推動方案（7月）
英文部分
Almada-Lobo, F. 2015. The Industry 4.0 revolution and the future of Manufacturing Execution Systems (MES). Journal of Innovation Management 3: 16-21.
Bordeleau, F. E., E. Mosconi, and L. Antonio Santa-Eulalia. 2018. Business Intelligence in Industry 4.0: State of the art and research opportunities. Paper presented at 51st Hawaii International Conference on System Sciences, Waikoloa, HI.
Brüggemann, H., and P. Bremer. 2015. Grundlagen Qualitätsmanagement. Wiesbaden: Springer.
Cao, H., P. Folan, J. Mascolo, and J. Browne. 2009. RFID in product lifecycle management: a case in the automotive industry. International Journal of Computer Integrated Manufacturing 22.(DOI: https://doi.org/10.1080/09511920701522981)
Carroll, S. T., T. A. Mahoney, T. H. Jerdee. 1963. The Job(s) of Management. Industrial Relations. 4(2), (p.97-110) (DOI: https://doi.org/10.1111/j.1468-232X.1965.tb00922.x)
Küpper, D., A. Heidemann, J. Ströhle, D. Spindelndreier, and C. Knizek. 2017. When Lean Meets Industry 4.0. Available at: https://www.bcg.com/publications/2017/lean-meets-industry-4.0.aspx#9-11110-1. Accessed: May 8, 2018.
Eckerson, W. W. 2015. Performance dashboards: measuring, monitoring, and managing your business. John Wiley & Sons. (DOI: 10.1002/9781119199984)
Elena, C. 2011. Business intelligence. Journal of knowledge management, economics and information technology, Romania.
Fink, L., N. Yogev, and A. Even. 2017. Business intelligence and organizational learning: An empirical investigation of value creation processes. Information & Management (DOI: https://doi.org/10.1016/j.im.2016.03.009)
Foidl, H., and M. Felderer 2016. Research Challenges of Industry 4.0 for Quality Management. Paper presented at Innovations in Enterprise Information Systems Management and Engineering, Germany.
Goel, D. 2017. What Is Industry 4.0 And How It Increases Machine Efficiency? Available at: https://thingtrax.com/2017/10/05/industry-4-0-increases-machine-efficiency/. Accessed: May 8, 2018.
Hehenberger, P. 2011. Computerunterstützte Fertigung: Eine kompakte Einführung. Berlin: Springer-Verlag.
Hozdić, E. 2015. Smart factory for industry 4.0: A review. Paper presented at 2014 IEEE International Conference on Industrial Engineering and Engineering Management, Malaysia. (DOI: 10.1109/IEEM.2014.7058728).
British Standards Institution. 2005. Quality management systems : fundamentals and vocabulary.No.3. England: British Standards Institution.
Koch, V., S. Kuge, R. Geissbauer, and S. Schrauf. 2015. Industry 4.0: Opportunities and challenges of the industrial internet. Available at: https://www.strategyand.pwc.com/reports/industrial-internet. Accessed: May 5, 2018.
Lasi, H., P. Fettke, H.-G. Kemper, T. Feld, and M. Hoffmann. 2014. Industry 4.0. Business & Information Systems Engineering 6(4): 239-242.
Li, B. H., B. C. Hou, W. T. Yu, X. B. Lu, and C. W. Yang. 2018. Applications of artificial intelligence in intelligent manufacturing: a review. Frontiers of Information Technology & Electronic Engineering, 18(1): 86-96. (DOI:10.1631/fitee.1601885)
Mittelstädt, V., P. Brauner, M. Blum, and M. Ziefle. 2015. On the visual design of erp systems the–role of information complexity, presentation and human factors. Procedia Manufacturing 3: 448-455. (DOI: https://doi.org/10.1016/j.promfg.2015.07.207)
Nikolic, B., J. Ignjatic, N. Suzic, B. Stevanov, and A. Rikalovic. 2017. Predictive manufacturing systems in industry 4.0: trends, benefits and challenges. Paper presented at 28TH DAAAM international symposium on intelligent, Croatia. (DOI: 10.2507/28th.daaam.proceedings.112)
Posada, J., C. Toro, I. Barandiaran, D. Oyarzun, D. Stricker, R. de Amicis, E. Pinto, E. Peter, J. Döllner and I. Vallarino. 2015. Visual computing as a key enabling technology for industrie 4.0 and industrial internet. IEEE computer graphics and applications 2: 26-40.
Putnik, G. D., M. Varela, R. Leonilde, C. Carvalho, C. Alves, V. Shah, H. Castro, and P. Ávila. 2015. Smart objects embedded production and quality management functions. International Journal for Quality Research (March).
Schuh, G., T. Potente, C. Wesch-Potente, A. R. Weber, and J. P. Prote. 2014. Collaboration Mechanisms to Increase Productivity in the Context of Industrie 4.0. Procedia CIRP, 19, 51-56. (DOI: https://doi.org/10.1016/j.procir.2014.05.016)
Singh, M., I. Khan, and S. Grover. 2012. Tools and techniques for quality management in manufacturing industries. Paper presented at the National Conference on Trends and Advances in Mechanical Engineering, Haryana.
Valdeza, A. C., P. Braunera, A. K. Schaara, A. Holzingerb, and M. Zieflea. 2015. Reducing complexity with simplicity-usability methods for industry 4.0. Paper presented at the Proceedings 19th triennial congress of the IEA, Australia (DOI: DOI: 10.13140/RG.2.1.4253.6809)
Yin, R. K. 1994. Case study research: Design and Methods. No.5. London: Sage Publications. |
| Description: | 碩士
國立政治大學
會計學系
105353027 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0105353027 |
| Data Type: | thesis |
| DOI: | 10.6814/THE.NCCU.ACCT.020.2018.F07 |
| Appears in Collections: | [會計學系] 學位論文
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