傳統產業製程自動化轉型之研究─以X公司為例

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題名:	傳統產業製程自動化轉型之研究─以X公司為例
作者:	李俊漢;Li, Chun-Han
貢獻者:	高階主管企管碩士班
關鍵詞:	自動化;automation
日期:	2025-06-04
上傳時間:	2025-10-17 12:14:29 (UTC+8)
出版者:	國立中央大學
摘要:	隨著全球製造業快速邁向高效率、智慧化與永續發展的趨勢，傳統中小型製造業，尤其是塑膠射出成型產業，正面臨前所未有的轉型壓力。在人力成本攀升、技術斷層日益嚴重、市場客製化需求提高以及環保法規趨嚴等多重挑戰下，過去仰賴經驗與人力操作的生產模式，逐漸無法滿足現今製造環境對品質穩定、交期彈性與成本控制的多元需求。這些問題對於規模有限、資源受限的中小企業而言更顯嚴峻，尤其在營運彈性、管理效率與客戶回應速度等方面，傳統製造模式的侷限性已日益明顯。塑膠成型產業長期處於台灣製造業供應鏈的中下游，承擔著高頻率、小批量、多樣化的代工任務，在面對技術更新快速與產業結構變動的情況下，轉型升級不僅關係到個體企業的存續與發展，更牽動整體產業價值鏈的優化與重組。唯有透過智慧製造與系統性變革的導入，傳統中小型塑膠成型廠方能突破過往營運瓶頸，重新建構其在全球供應體系中的角色與競爭優勢。本研究以台灣一間具有代表性的中型塑膠成型廠X公司為個案，針對其傳統人工作業比重高、良率波動大、資訊回饋延遲等經營瓶頸，探討如何透過製程自動化與資訊整合來優化整體生產流程。研究重點包括：分析生產中埋入成型、CNC加工與尺寸量測等關鍵工段的痛點；設計並導入機械手臂、自動嵌件平台與即時監控模組等設備；進而評估自動化升級對產能、品質與營運管理所產生的綜合性影響。本研究同時延伸至管理層面，深入探討中小型製造企業在資源有限、技術門檻高、組織結構扁平的現實下，如何以低風險、高回報的策略方式推動轉型，並從實務角度提出可操作的導入節奏與管理建議。本研究顯示，製程自動化不僅是解決勞力依賴與效率瓶頸的技術手段，更是中小企業建立「系統性管理能力」的轉捩點。透過即時生產數據的建立與應用，企業得以更精準掌握生產狀況，提升決策效率與品質穩定性，進而形成持續改善與風險預警的管理體制。在這樣的基礎上，企業逐步具備將管理邏輯由「人治」邁向「數據治理」的能力，為未來導入智慧製造、強化彈性排程與永續經營策略奠定關鍵基礎。此外，自動化與資訊化的導入並非單一部門的改善行動，而是企業整體經營思維的轉變起點。組織在轉型過程中需同步進行人力資源再培訓、跨部門協作重構與營運流程再設計，才能真正發揮技術升級的價值。本研究強調，「漸進式導入」、「瓶頸導向」、「模組化升級」等策略，對於中小型製造企業而言，具備實務可行性與良好的風險控管效益。企業若能以中長期視角擘劃智慧製造藍圖，不僅能有效控管初期轉型的不確定性，更能逐步建立因應未來產業變局的彈性韌性。未來如何將現有轉型成果擴展至供應鏈整合、智慧排程與能源效率管理等層面，將是企業從「製造升級」走向「智慧治理」的關鍵課題，也為傳統製造業提供一條兼顧效益與可持續發展的進化路徑。;As global manufacturing continues to shift towards higher efficiency, digitalization, and sustainability, traditional small and medium-sized enterprises (SMEs), especially those in the plastic injection molding industry, are facing unprecedented transformation pressures. Rising labor costs, an aging skilled workforce, increasingly customized market demands, and tightening environmental regulations have rendered legacy production methods—reliant on manual labor and experience—insufficient to meet modern standards in quality consistency, delivery flexibility, and cost control. For resource-constrained SMEs, these challenges are even more daunting. The plastic molding industry, a key mid-to-downstream player in Taiwan′s manufacturing supply chain, must confront these realities or risk being marginalized in an increasingly automated and value-driven global ecosystem. This study adopts a case-based approach to examine the transformation journey of X Company, a representative medium-sized plastic molding enterprise in Taiwan. The research identifies major bottlenecks in manual-intensive production stages such as embedded molding, CNC machining, and dimensional measurement. It then explores how automation solutions—such as robotic arms, auto-insertion systems, and real-time monitoring modules—can be strategically implemented to optimize workflow, stabilize quality, and improve operational transparency. Further, the study analyzes how SMEs with limited resources, flatter organizational structures, and high dependence on experienced labor can adopt phased, low-risk strategies for transformation, offering practical insights into sequencing and implementation. The findings reveal that process automation is not merely a solution to reduce labor dependency or improve efficiency; it represents a crucial turning point for SMEs to develop systemic management capabilities. By leveraging real-time production data, companies can enhance visibility, facilitate rapid decision-making, and establish predictive quality and risk management systems. More importantly, this transformation signifies a shift from person-dependent decision-making to data-driven governance. Furthermore, this shift requires organizational-wide alignment, including workforce reskilling, cross-department collaboration, and operational restructuring to realize the full value of technological upgrades. The study highlights the practical relevance and risk mitigation value of incremental deployment, bottleneck targeting, and modular upgrades in SME settings. It encourages enterprises to craft long-term visions for smart manufacturing and to gradually evolve into more resilient and responsive organizations. Extending these efforts to areas such as supply chain integration, intelligent scheduling, and energy optimization will be the next step from "manufacturing upgrades" to "intelligent governance," offering traditional manufacturers a pathway that balances efficiency with sustainability.
顯示於類別:	[高階主管企管（EMBA）碩士班] 博碩士論文

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