傳統醫療手套業製造執行系統（MES）開發與導入實證－以P公司為例;Development and Implementation of a Manufacturing Execution System (MES) in the Traditional Medical Glove Industry: A Case Study of Company P

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Title:	傳統醫療手套業製造執行系統（MES）開發與導入實證－以P公司為例;Development and Implementation of a Manufacturing Execution System (MES) in the Traditional Medical Glove Industry: A Case Study of Company P
Authors:	張筑雅;Chang, Chu-Ya
Contributors:	資訊工程學系在職專班
Keywords:	製造執行系統;傳統製造業;系統開發
Date:	2026-01-16
Issue Date:	2026-03-06 18:51:50 (UTC+8)
Publisher:	國立中央大學
Abstract:	醫療手套業屬於典型的連續式製程，其生產線以模具掛載軌道為核心，手套需依序經過清洗、浸漬、烘乾與硫化等多道工序，對製程穩定性與品質管理具有高度要求，然而，傳統手套產線多仰賴人工方式進行品質檢驗，導致品質數據蒐集延遲與缺模等異常狀況無法及時掌握，進而影響產品品質與產線效率，為改善上述製程管理與品質監控之問題，本研究以實際醫療手套產線為研究對象，開發並導入一套輕量化製造執行系統（MES），整合企業資源規劃系統（ERP）工單資訊、監控系統（SCADA）設備參數以及品質檢驗數據，並透過光電計數器與即時儀表板，建立缺模率即時監控與異常警示機制，以數位工具實現即時數據驅動，提升製程透明度與管理效能。本研究採用系統設計與實務驗證並行之研究方法，將所建構之MES實際部署於個案工廠進行驗證。實驗結果顯示，系統有效降低缺陷發生率，提升產線管理效率，研究成果展現即時監控與數據驅動管理的優勢，並為傳統醫療手套產業之數位轉型提供具體且可行的實證依據與參考。;The medical glove industry is characterized by a continuous manufacturing process in which production lines are centered on mold-mounted conveyor tracks. Traditional glove production relies heavily on manual quality inspection, resulting in delayed data collection and limited real-time visibility of quality issues. Among these issues, missing molds are a major common cause of defects such as pinholes, uneven thickness, and surface imperfections. To address these challenges, this study develops a lightweight Manufacturing Execution System (MES) that integrates work order information from an Enterprise Resource Planning (ERP) system, process parameters from a Supervisory Control and Data Acquisition (SCADA) system, and quality inspection data. Photoelectric sensors and real-time dashboards are introduced to enable real-time monitoring and abnormality alerts for mold missing rates, thereby improving process transparency and production management efficiency. This study adopts a combined approach of system design and practical validation. Experimental results indicate that the proposed system effectively reduces defect occurrence rates and enhances production line management efficiency, providing practical empirical evidence for digital transformation in the traditional medical glove industry.
Appears in Collections:	[Executive Master of Computer Science and Information Engineering] Electronic Thesis & Dissertation

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