結合SQL及NoSQL方法驗證跨領域資料庫整合之研究
－以塑膠模具產業為例

隨著紅色供應鏈的崛起、全球勞動力的短缺，造成全球工資大幅上升，加上大量客製化概念的興起，使得現今的製造產業必須轉型，為此各國紛紛提出產業戰略應對方案。2012年，製造工業大國德國，揭示了工業4.0時代的來臨。為了因應全球競爭趨勢，協助製造業升級，我國提出生產力4.0策略方案，其中部分參酌德國4.0的虛實化系統概念，強調將以智慧機器人、物聯網、大數據分析為3大科技主軸，提升產業之競爭優勢，生產力4.0的核心作法是推動產業朝設備智動化、系統虛實化及工廠智慧化發展來提升產品附加價值及優化台灣產業結構，以創造產業下一波的成長新動能。以台灣塑膠模具產業為例，塑膠零組件的生產跨越的領域甚廣，從模具設計、模具製造到射出成形，但大部分公司只限於單一領域欠缺整合性的系統，難以達到生產力4.0策略方案的標準。有鑑於此，本研究將設計一套雲端整合平台，以資料治理為中心的基礎概念重新設計整合，將分散在各領域中的資料庫同步至整合資料庫中。本研究經過系統雛形與專家驗證之後，本研究所提出的模具生命週期模型確實能夠應用於塑膠模具產業邊陲長流程，利用此彈性化的變更定義的物件，對於縮短虛實落差與資訊整合作出貢獻。

關鍵字

工業4.0 ；大數據資料治理；資料生命週期； NoSQL ；雲端資料庫

並列摘要

With rise of the “Red Supply Chain”, global shortage of labor, resulting in global wages sharply arising. Also, the growing of the “Mass Customization”, nowadays make manufacturing industry need to be restructured. For these reasons, industrial countries have made strategies to face it. In 2012, Germany announced the industrial era 4.0 is coming. In response to the trend of global competition to help upgrade the manufacturing sector, Taiwan has proposed the “Productivity 4.0 Policy”, part of the actual situation of the German system concept 4.0. But in Taiwan, the “Productivity 4.0 Policy” emphasize on the Intelligent Robot, Internet of Things and the Big Data, these three major technologies, will lift the industry competitive advantage, Productivity 4.0’s core conception is to promote the Automation intelligence equipment, the Cyber-Physical System and the Smart factory to enhance the development of plant intelligence value-added products and optimize the industrial structure in Taiwan and create new growth momentum next wave of industry. Take Taiwan plastic mold industry for example, in plastic components production across the wide, from mold design, tooling to injection molding. But most companies is limited to a single field and lack of integration of the system, it is hard to achieve Productivity 4.0 Policy‘s standards. In view of this, this study will design a cloud integration platform, with the data governance as the basis concept to integrate data from various fields to the integrative database. After the expert verification and system prototyping, mold life cycle model proposed can be applied in the plastic mold industry’s long flow in this study. In the use of this flexible definition of the object changes, shortening the cyber-physical gap and contribute to the integration of information.

並列關鍵字

Industry 4.0 ； Big Data ； Data governance ； Data life cycle ； NoSQL ； Cloud Database

參考文獻

王怡惠. (2015). 從工業4.0看我國生產力4.0之挑戰. 臺灣經濟研究月刊, 38(8), 111–119.

陳美勇, & 鐘秉剛. (2015). 工業4.0計畫中智慧型機器人發展之趨勢. 中等教育, 66(3), 6–13. http://doi.org/10.6249/SE.2015.66.3.01

Benbasat, I., Goldstein, D. K., & Mead, M. (1987). The case research strategy in studies of information systems. MIS Quarterly, 369–386.

Cattell, R. (2011). Scalable SQL and NoSQL Data Stores. SIGMOD Rec., 39(4), 12–27. http://doi.org/10.1145/1978915.1978919

Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165–1188.

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結合SQL及NoSQL方法驗證跨領域資料庫整合之研究－以塑膠模具產業為例

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