「工業3.5」之先進智慧製造系統架構：半導體智慧製造為例

Industry 3.5 Framework of an Advanced Intelligent Manufacturing System: Case Studies from Semiconductor Intelligent Manufacturing

本研究提出「工業3.5」作為工業3.0和工業4.0之間的混合策略，整合物聯網、大數據分析、資源調度與最佳化等技術，發展先進智慧製造系統架構，並以半導體製造實際問題為例，發展模組化的解決方案，以檢驗研究效度。事實上，工業4.0仍在演化中，本研究提出之工業3.5架構已有智慧製造的實踐案例，可以作為其他產業發展並實現先進智慧製造的藍圖和參考依據，先在既有基礎上，發展智慧製造所需的大數據分析和最佳化彈性決策能力，才能在未來工業4.0基礎更成熟時發揮更大效益。 This paper proposes that Industry 3.5 is a hybrid strategy that enables intelligent manufacturing with use of the big data analytics and digital decision-making processes of Industry 4.0 and the existing manufacturing system of Industry 3.0. The proposed strategic framework integrates leading technologies such as the Internet of Things, big data analytics, resource allocation, and optimization to develop an advanced intelligent manufacturing system framework. To determine the feasibility and validity of the proposed Industry 3.5 framework, this study reviewed a number of empirical studies concerning semiconductor manufacturing. The results indicated that the proposed Industry 3.5 is viable and can be used as an effective roadmap and reference to empower the migration of various industries to Industry 4.0 through adoption of advanced intelligent manufacturing, big data analytics, flexible decision-making, and optimization.

This paper proposes that Industry 3.5 is a hybrid strategy that enables intelligent manufacturing with use of the big data analytics and digital decision-making processes of Industry 4.0 and the existing manufacturing system of Industry 3.0. The proposed strategic framework integrates leading technologies such as the Internet of Things, big data analytics, resource allocation, and optimization to develop an advanced intelligent manufacturing system framework. To determine the feasibility and validity of the proposed Industry 3.5 framework, this study reviewed a number of empirical studies concerning semiconductor manufacturing. The results indicated that the proposed Industry 3.5 is viable and can be used as an effective roadmap and reference to empower the migration of various industries to Industry 4.0 through adoption of advanced intelligent manufacturing, big data analytics, flexible decision-making, and optimization.