面對網路的日益普及、技術發展日新月異、商業模式隨著萬物聯網不斷創新，全球產業無不受到大小不一的震盪，且為了因應全球共同面臨四大問題：勞動力減少、物料成本上漲、產品與服務生命週期縮短、需求方之各種需求變化，各行各業皆體認到勢必得走上轉型升級的道路。就製造發達國家而言，相較於服務業，製造業產業關聯效果高，產業帶動效果大，具有較高生產力與出口能力，故身處物聯網的發展與製造業服務化浪潮，各國無不積極面對與創造新一波的製造業復興和革命。根據全球最大的專業服務機構PwC最新調查報告2016 Global Industry 4.0 Survey指出，在2020年以前，全球製造業每年投資在工業4.0的金額將超過9,000億美元，工業4.0預期在5年後可為企業平均減少43%的成本及增加35%的營收。
工業4.0智慧製造是跨領域且涉及相當廣泛的製造革新工程，本研究透過蒐集國內外相關的文獻與分析，探討工業4.0的形成背景、簡述世界主要國家相應的產業發展政策方向，接著介紹支撐智慧製造發展的相關資通訊科技項目。台灣製造業以代工模式曾經創造令各國刮目相看的經濟奇蹟，然而在工業4.0的時代，進行工業變革之際，需要產、官、學研共同深思未來產業發展的策略，如何結合台灣的實際現況與優勢，發現潛在的機會與突破點。因此，本論文第一項研究提出一個完整的技術地圖產生方法論（共有7個步驟），從2015年台灣提出的生產力4.0發展發案中萃取智慧製造19項關鍵技術，並對應至四層架構中(感知層、整合層、智能判斷層、回應層)，召開專家會議與專家問卷，產生19項智慧製造關鍵技術的市場成熟與技術成熟趨勢分析、關聯分析，根據技術關聯性畫出技術地圖，最後請專家針對政策與產業發展給予台灣未來智慧製造具體建議。
除此之外，本研究以社會認知理論（Social Cognitive Theory, SCT）為核心，針對台灣製造業的現況，發展企業是否願意投入智慧製造的研究模式，除期望能藉此進一步解釋影響企業投入智慧製造的因素有哪些，更希冀能夠找出哪些因素是促成企業投入智慧製造與否的核心要素。社會認知理論對於人類如何面對環境，及其所採行的行為提出了相當重要的觀點，本研究循序探討需求市場成熟度、供給市場成熟度、政府補貼政策、自我效能與期待產出等面向，如何影響企業投入智慧製造意願，期能成為政府推動、產業投入、學研單位進一步研究台灣工業4.0的基礎輪廓，並給予相關單位發展智慧製造之具體建議。研究共回收188份有效網路問卷，結果發現，知覺需求市場成熟正向顯著影響自我效能與期待產出，自我效能與期待產出正向顯著影響企業投入智慧製造的意願。
最後，綜合研究一（質化研究）與研究二（量化研究）深入探討台灣智慧製造發展現況與趨勢與企業投入意願，本論文針對這兩項研究結果，提出學術與管理意涵，期能提供產業及政府政策有新的思維，保持台灣於全球智慧製造產業供應鏈的競爭優勢。

The Forth Industrial Revolution (Industry 4.0) integrates all current technologies such as sensors, wireless networks, Internet of Things (IoT), robotics, artificial intelligence and information management systems to create a Cyber-Physical System (CPS) and smart factories. According to a 2016 PricewaterhouseCoopers (PwC) survey, through 2021 manufacturing enterprises globally expect that the successful implementation of Industry 4.0 initiatives will increase annual revenues by an average of 35% and reduce costs by an average of 43%. Moreover, global industrial product companies intend to make annual investments averaging US$907 billion through 2020.
Industry 4.0 is still in its adolescence and each country varies in its industrial conditions and how it is proceeding to promote and implement concepts and practices. Industry 4.0 represents a revolution in engineering which integrates a wide range of industrial and technological fields. This study conducted two studies, including qualitative study and quantitative study to understand the smart manufacturing technologies development trend, technology roadmap and critical factors influence enterprise investment intention of smart manufacturing in Taiwan.
First, a smart manufacturing key technology architecture is proposed which classifies the nineteen key technologies into four layers: sensor layer, an integration layer, an intelligent layer and a response layer. A technology roadmap is developed as a context for the analysis of correlations between technology applications and industry maturity. Technologies were defined through interviews with industry experts, and the correlation results are used to create a correlation matrix for the current status of smart manufacturing in Taiwan, including market maturity, technology maturity and correlation of key technologies. Suggestions for future smart manufacturing industry development in Taiwan were also collected.
Second, drawing on Social Cognitive Theory (SCT), this study develops a model to identify impact factors for enterprise intention to invest in smart manufacturing. The model was tested using online survey data collected from 188 R&D and project development professionals from manufacturing and high-tech firms in Taiwan. The results showed that perceived demand market maturity significantly affects self-efficacy and outcome expectancy, and thus influences enterprise intention to make Industry 4.0 related investments, while the impacts of perceived supply market maturity and government subsidy policies were less significant. The results can serve as a useful reference for Industry 4.0 investment and policy making for government agencies, industry, and researchers, while providing insight for the future development of smart manufacturing.

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