中小企業對全球與台灣經濟發展有高度貢獻與重要性，但隨著數位化與工業4.0的興起，中小企業與半導體產業相較之下，中小企業較無法投入大量的資金與資源來導入大數據、人工智慧、物聯網等新興技術，但各企業為了提升其資訊化的程度，皆會導入企業資源規劃(Enterprise Resource Planning , ERP)、現場生產控制(Shop Floor Tracking, SFT)等套裝資訊軟體來輔助現場管理，並期望各製程能按照先進先出(First In First Out, FIFO)的順序進行生產。
在實際的製造現場中，由於ERP、SFT等套裝軟體的格式、所能呈現的資訊都是固定的，使得製造現場仍無法按照FIFO的順序進行生產，以本案例光學眼鏡製造公司為例，案例現況已導入ERP、SFT等套裝資訊，但在實際的製造現場中，由於時常會遇到材料齊料、委外加工等眾多限制，導致套裝軟體無法實際滿足各企業現場的實際需求，造成當前軟體提供的資訊未被充分利用及需要許多額外的人工作業，為了能有效的解決上述問題，本研究將透過結合精實生產及工業4.0，強調以易取得的數位工具，運用智慧製造三要素建立出複雜度適中的智慧化系統來支持TPS的兩大支柱並持續進行改善，而此改善循環又稱為自働生產管理環(Jidoka-JIT Cycle, JJC)。
本研究在實際的改善實施上，會先在精實理念之下利用價值流程圖4.0 (Value Stream Mapping 4.0, VSM 4.0)針對案例公司各製程進行現況分析，再利用JJC的概念根據案例公司各製程的需求分別建構出精實資訊系統來輔助現場管理，並使得案例公司得以按順序生產，同時藉由資料可用率、資料使用率、數位化比率、資訊作業流程時間(Process Time)、資訊作業流程所需步驟、因資料交換、人員參與產生之節點數量、生產時間(Lead Time)等七項績效指標來驗證改善成效，導入系統後可由研究結果得知案例公司整體資訊作業流程時間降低了40.6%；整體資訊作業流程步驟減少了12.5%；整體節點數量減少了36.84%；整體生產時間降低了8.68%，以此證明中小企業在數位轉型的過程中，資訊流程的改善與按順序生產的重要性。

Small and medium-sized enterprises have made an extremely important contribution to the global and Taiwan economic development, but with the rise of digitalization and Industry 4.0, the semiconductor industry, small and medium-sized enterprises are less able to invest a lot of funds and resources to import big data , artificial intelligence, Internet of things and other emerging technologies. In order to improve the degree of informatization, each enterprise will introduce Enterprise resource planning(ERP), Shop Floor Tracking(SFT) and other packaged information software to assist on-site management, and expect each process to be produced in the order of First-in-First-Out (FIFO).
On the actual manufacturing field, the fixed format and information that can be presented by packaged software such as ERP and SFT, which the manufacturing field still cannot follow the order of FIFO to manufacturing. Take the optical glasses manufacturing company for example, At present, package software like ERP and SFT has been imported, but on the actual manufacturing field, many restrictions are always caused by outsourcing , material shortage, and different processing sequences, which the package software cannot actually meet the actual conditions of each manufacturing field’s demand. This caused not only the information provided by the current software to be underutilized, but also made the manufacturing field still require a lot of extra manual work.
In order to effectively solve the above problems, this study will combine lean production and Industry 4.0, emphasizing easy-to-obtain digital tools, and use the three elements of smart manufacturing to establish an intelligent system with moderate complexity to support the two pillars of TPS and Continuous improvement, and this improvement cycle is also called Jidoka-JIT Cycle.
In terms of the actual implementation of improvement, this study will first use Value Stream Mapping 4.0 to analyze the current situation of each process of the case company under the lean concept, and then use the concept of JJC to construct a lean information system according to the needs of each process of the case company to assist on-site management, and enable the case company to produce in sequence. At the same time, to verify the improvement effect through data availability, data usage, digitization ratio, Process time, steps required for information operation process, and number of nodes generated and personnel participation, Lead time caused by data exchange performance indicators. After the system is imported, the research results show that the overall Process Time of the case company has been reduced by 40.6%; the overall information operation process steps have been reduced by 12.5%; the overall number of nodes has been reduced by 36.84%; the overall Lead Time has been reduced by 8.68%, which prove that the improvement of information flow and sequential production are important process for small and medium-sized enterprises to transform in digital industries.

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