傳統工廠最主要的問題是生產線沒有系統性的規劃及整合，生產數據是依靠人工的方式進行採集，因此資料分析的效率非常的低，準確度也不高，管理者無法依靠即時的生產資訊進行有效的決策。另外巨量的資料儲存也是一項問題，當數據以紀錄紙或Excel表進行整理時，資料可能會隨著管理人員的流動或其他因素造成數據流失。 智慧工廠是藉由感測器和網路的方式將設備互相串連，透過製造執行系統 （Manufacturing Execution System，MES）整合出的生產數據，管理者可以用來即時掌握製造活動中的在製品WIP (Work In Process)、原料、設備、生產狀況與實際生產結果。製造執行系統可以實現產品數字化製造，提高產品製造能力，降低製造成本，並提高企業競爭能力。 本研究是探討傳統汽車製造廠推動導入製造執行系統專案，運用DSM (Design Structure Matrix,設計結構矩陣)的方式，解析專案各階段的關聯性和相依性，設法驗證其彼此關聯的正確性，來決定執行專案的目標和優先順序，確保專案能順利完成。 ;The main problem of traditional factories is that there is no systematic planning and integration of production lines, and production data is collected by manual methods. Therefore, the efficiency of data analysis is very low, and the accuracy is not high. Managers cannot rely on real-time production information. Effective decision-making. In addition, the huge amount of data storage is also a problem. When the data is sorted with record paper or Excel sheets, the data may be lost due to the flow of management personnel or other factors. The Smart factories connect devices to each other by means of sensors and networks. Through the production data integrated by the Manufacturing Execution System, managers can use it to instantly grasp the Work In Process, raw materials, equipment, production status and Actual production results. The Manufacturing Execution System can realize digital manufacturing of products, improve product manufacturing capabilities, reduce manufacturing costs, and improve enterprise competitiveness. This research is to explore the introduction of manufacturing execution system projects by traditional automobile manufacturers, use the design structure matrix to analyze the relevance and dependency of each stage of the project, and try to verify the correctness of their correlations to determine the goals and priorities of the project Sequence to ensure that the project can be successfully completed
