升級智慧製造關鍵因素之轉型優先順序探討

工業4.0及物聯網技術運用發展，應用系統需重新整合為具有開放式架構的智慧系統導入製造業，依其產生的綜合效應將製造業打造成智慧工廠，過往研究針對製程因素改善為目的，進而降低成本與滿足客戶多樣性的需求，提供企業從製造到銷售端的解決方案。本研究以資訊系統整合數據架構的方式為基礎，探討資訊系統介入傳統製造業後所演化出的智慧製造可能促成之服務創新，分析產業轉型升級出關鍵因素發展優先順序。考量層級分析（AHP）研究方法可針對多目標與多評估準則之不確定情況下，匯集專家學者意見，簡明扼要問題並分析組成之因素，問卷回收175份有效樣本針對製造業且具備該產業代表性或成立至少20年以上、面臨企業轉型問題、皆為智慧製造資訊軟體、硬體提供服務業。研究結果顯示，構面前三位排序分別為：企業學習能力、虛實整合能力、設備智慧程度，其所屬之評估準則發展順位有利評估智慧製造關鍵因素對於服務創新模式影響因子。

關鍵字

智慧製造；工業物聯網；網宇實體系統；製造執行系統

並列摘要

With the application and development of Industry 4.0 and Internet of Things technology, the application system needs to be re-integrated into a smart system with an open architecture and imported into the manufacturing industry, and the manufacturing industry will be turned into a smart factory according to the comprehensive effect. To reduce the costs and meet the diverse needs of customers, we can provide solutions from manufacturing to sales. Based on the way of information system for integrating the data architecture, this research explores the service innovation that was facilitated by smart manufacturing evolved after information system intervenes in traditional manufacturing industry, and analyzed the development priorities of key factors in industrial transformation and upgrading. Consideration Hierarchy Analysis (AHP)research method can gather the opinions of experts and scholars under the uncertain situation of multi-objective and multi-evaluation criteria, concisely analyze the problem and analyze the constituent factors, 175 valid samples were collected from the questionnaire for the manufacturing industry, It is representative of the industry or has been established for at least 20 years, faces the problem of enterprise transformation, and provides the services for intelligent manufacturing information software and hardware. The research results show that the prior three rankings of the analysis are: enterprise learning ability, virtual-real integration ability, and equipment intelligence level. The development on the sort of order for the evaluation criteria to which they belong is favorable for evaluating the impact factors of key factors of smart manufacturing on service innovation models.