| 研究生: |
林書帆 LIN SU FAN |
|---|---|
| 論文名稱: |
半導體後端製程自製或外包之分析探討 A Study on Make-or-Buy Decisions in Semiconductor Backend Processe |
| 指導教授: | 曾富祥 |
| 口試委員: | |
| 學位類別: |
碩士 Master |
| 系所名稱: |
管理學院 - 工業管理研究所在職專班 Executive Master of Industrial Management |
| 論文出版年: | 2025 |
| 畢業學年度: | 113 |
| 語文別: | 中文 |
| 論文頁數: | 37 |
| 中文關鍵詞: | 半導體後端製程 、自製或外包 |
| 相關次數: | 點閱:13 下載:0 |
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在全球供應鏈高度分工與技術快速演進的趨勢下,企業如何有效配置有限資源,以提升營運效率與整體競爭力,已成為關鍵課題。尤其在半導體產業中,後端製程如測試與封裝,涉及高度技術門檻、設備投資與交期控管,使企業在自製與外包兩種策略之間,需審慎權衡利弊。此類決策不僅影響成本與效率,也關係到技術掌握程度與品質穩定性,進而牽動整體供應鏈整合的效能。
本研究聚焦於半導體後端製程的營運策略選擇,透過文獻回顧與產業專家訪談,歸納出技術服務、成本、時間與品質四大構面,並細分為十二項子構面,以建構具操作性之層級架構。研究進一步導入層級分析法(AHP),設計成對比較問卷,邀請半導體與高科技產業專家進行填答,量化各構面在決策中的相對重要性,並透過一致性檢驗確保資料可靠性。
分析結果顯示,企業最重視成本與時間構面,特別是在資源投入與產品上市時效方面,為主要考量因素。技術差異化與良品率亦被視為關鍵指標。本研究所建構之模型,具邏輯性、一致性與延伸性,除可應用於半導體後端製程外,亦適用於其他高科技產業之資源配置決策情境。
關鍵字:自製與外包、半導體製程、層級分析法(AHP)
In the context of global supply chain specialization and rapid technological progress, resource allocation has become a critical concern, particularly for the semiconductor industry. Backend processes such as testing and packaging involve technical complexity, high capital investment, and strict time control. Enterprises must choose between in-house and outsourcing strategies, each with implications for cost, control, and product quality.
This study explores strategic decision-making for semiconductor backend operations. Based on literature review and expert interviews, four decision dimensions—technical service, cost structure, time efficiency, and quality control—are identified and expanded into twelve sub-criteria. The Analytic Hierarchy Process (AHP) is applied to evaluate the relative importance of each factor using pairwise comparison questionnaires completed by industry professionals.
Findings indicate that cost and time are the most influential criteria, especially in labor and equipment investment, development cycles, and delivery control. Technical differentiation and yield rate also emerge as key factors for maintaining competitiveness. The resulting AHP model combines expert knowledge with quantitative analysis to offer a structured, consistent, and practical framework for make-or-buy decisions.
Beyond its relevance to the semiconductor industry, the model has potential for application across various high-tech sectors dealing with outsourcing and capability development. It supports better resource planning in dynamic environments.
Keywords: Make-or-Buy Decision, Analytic Hierarchy Process (AHP), Multi-Criteria Decision Making (MCDM), Resource Allocation Strategy
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