製藥業的設備管理因其高度監管特性，必須在符合法規與追求效率間取得平衡，一方面須嚴守法規標準以確保藥品安全及品質；另一方面需提升企業營運效率以維持市場競爭力。然而，在現行管理架構中，傳統作業模式如紙本記錄和分散的資訊系統，導致資訊孤島、作業效率降低、數據追溯性不足，成為數位轉型的阻力。
本研究以一間製藥公司為本研究之案例公司。在研究方法上，首先根據資訊流圖分析現行設備維修與保養流程，識別資訊浪費與瓶頸。接著，採用低程式碼開發平台與雲端的軟體即服務之理念，建構一套雲端設備管理系統，其核心在於整合自働生產管理環(Jidoka-JIT Cycle, JJC)之理念，融合企業內部既有工具與外部雲端平台，透過雲端技術提升數據處理效率，並使用如Power Apps與Power BI等工具，降低數位化門檻，促進員工參與流程改善，實現數據集中管理、流程自動化與視覺化監控。最後本研究整合層級分析法（Analytic Hierarchy Process , AHP）與失效模式與影響分析（Failure Mode and Effects Analysis, FMEA），透過數據驅動的局部權重計算，克服傳統風險優先數(Risk Priority Number, RPN)的限制，更客觀地進行風險排序。
實證分析結果表示，導入低程式碼雲端系統後，設備異常通報時間縮短90%，追蹤時間縮短99%。半年內，設備可動率提升至98.6%（提升4.2%），平均停機時間下降46.6%，異常數量減少69.23%。AHP-FMEA風險評估方法相較傳統FMEA產生統計上極顯著的差異排序，提高風險鑑別度，並能識別累積性風險。
本研究的主要貢獻在於：一、提供整合低程式碼平台、雲端技術、精實管理與AHP-FMEA的製藥業設備管理解決方案；二、驗證低程式碼工具在受規範環境下快速開發客製化系統的可行性與效益；三、提出並實證改良的AHP-FMEA方法能更精準進行風險評估優化資源配置；四、量化數位轉型在提升營運效率與設備績效上的具體成果。

Equipment management in the pharmaceutical industry, due to its highly regulated nature, must strike a balance between regulatory compliance and the pursuit of efficiency. On one hand, it must strictly adhere to regulatory standards to ensure drug safety and quality; on the other hand, it needs to enhance operational efficiency to maintain market competitiveness. However, within the current management framework, traditional operational modes such as paper-based records and dispersed information systems lead to information silos, reduced operational efficiency, and insufficient data traceability, becoming obstacles to digital transformation.
This research focuses on a case study of a pharmaceutical company. In terms of methodology, current equipment maintenance and repair processes were first analyzed using information flow diagrams to identify information waste and bottlenecks. Subsequently, a cloud-based equipment management system was developed using a low-code development platform and cloud Software-as-a-Service (SaaS) principles. Its core lies in integrating the Jidoka-JIT Cycle (JJC) philosophy, merging the company's existing internal tools with external cloud platforms. Cloud technology enhances data processing efficiency, and tools such as Power Apps and Power BI are used to lower digitalization barriers, promote employee participation in process improvement, and achieve centralized data management, process automation, and visual monitoring. Finally, to enhance the accuracy of risk assessment, this study integrates the Analytic Hierarchy Process (AHP) with Failure Mode and Effects Analysis (FMEA), employing data-driven local weight calculations to overcome the limitations of traditional RPN methods and rank risks more objectively.
Empirical analysis results indicate that after the implementation of the low-code cloud system, equipment abnormality reporting time was shortened by 90%, and tracking time by 99%. Within six months, equipment availability increased to 98.6% (an improvement of 4.2%), average downtime decreased by 46.6%, and the number of abnormalities was reduced by 69.23%. The AHP-FMEA risk assessment method, compared to traditional FMEA, produced statistically highly significant differences in risk ranking, improved risk differentiation, and enabled the identification of cumulative risks.

The main contributions of this research are: 1. Providing a pharmaceutical equipment management solution that integrates low-code platforms, cloud technology, Lean Management, and AHP-FMEA. 2. Validating the feasibility and benefits of using low-code tools for the rapid development of customized systems in a regulated environment. 3. Proposing and empirically validating an improved AHP-FMEA method for more accurate risk assessment and optimized resource allocation. 4. Quantifying the concrete outcomes of digital transformation in enhancing operational efficiency and equipment performance.

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