臺灣博碩士論文加值系統

隨著高科技公司的規模日益龐大，工程人員所扮演的角色也越來越重要，由於工程人員的工作內容屬隨機性的支援生產現場，不定時的解決過程中的製造問題，以保持生產流暢的作業，例如機台參數設定等。因而產量越大，機台發生問題的機會變多，工程人員的工作負荷便會增加；但產品越複雜，生產過程發生問題的機率也會增加，同樣會影響工程人員的工作負荷。一般企業在評估工程人員的工作負荷時，僅以產量和人數比值當成調整工程部門人力的參考，但只以產量作為影響因素卻無法反應出工程人員的工作現況，學術上雖然可以使用繁雜的數學模式，定出所有變因再求解所需人力，但企業在執行上確有不便。因此本研究擬提出一評估模式包含產量及產品複雜度，利用層級分析法（Analytic Hierarchy Process）衡量產品複雜度，同時探討學習曲線對於此評估模式的影響，期使本模式能兼具理論與實務的效用。

With the expansion of high-tech companies, engineering personnel play a role of growing importance. Engineering personnel mainly work as on-the-scene, immediate support, such as solving the problems created during the manufacturing process to maintain the flow line of operation and setting parameters of machines as well. The larger the production quantity is, the more problems will be caused by machines, and also the more work load of the engineering personnel is. Meanwhile, as products become further complicated, problems in the manufacturing process are more likely to occur and this also leads to the heavy burden of workers. In general, as industries evaluate the work load of engineering personnel, the ratio of production to population is served as reference to adjust manpower in the engineering department. Only the amount of production to be considered an influential factor cannot reflect the present situation of engineering personnel. In the academic study, detailed mathematical formulas can be applied to find out all the variants and then figure out the manpower needed. In business, it is, however, inconvenient to practice simply by that. Therefore, an evaluation model, including production amount and product complexity, is proposed by this study. Analytic Hierarchy Process is used to measure the complexity of products. At the same time, learning curve is studied to realize its influence on the evaluation model. It is expected that the model carries out both the effects of theory and reality.

摘 要i
Abstractii
誌 謝iii
目 錄iv
表 目 錄vii
圖 目 錄viii
第一章 緒論1
1-1 研究背景1
1-2 研究動機2
1-3 研究目的3
1-4 研究流程3
1-5 論文架構6
第二章 文獻探討7
2-1 人力資源管理7
2-2 工程部門人力需求規劃8
2-3 AHP簡介9
2-3-1 AHP發展與假設9
2-3-2 AHP的應用14
2-3-3 AHP基礎理論15
2-3-4 一致性檢定17
2-3-5 AHP評估尺度19
2-3-6 最大特徵值（Eigenvalue）及特徵向量（Eigenvector）20
2-4 學習曲線簡介23
2-4-1學習曲線的意義23
2-4-2學習曲線的模式25
第三章 模式建立28
3-1問題特性28
3-2模式建立28
第四章 案例應用34
4-1 案例公司簡介34
4-2 資料收集34
4-3 案例結果40
4-4學習曲線的敏感度分析47
4-5結果與討論50
第五章 結論52
5-1 結論52
5-2 後續研究建議53
參考文獻55
附錄A59
附錄B60
附錄C66
表 目 錄
表2-1 隨機指標表19
表2-2 評比尺度表20
表4-1 1996年各產品相對複雜度權重35
表4-2 1997年新增產品與PDIP的相對權重36
表4-3 1996-2000年新增產品的相對權重37
表4-4 各半年度工程部門人數38
表4-5 1996年到2000年每半年的工程部門人數與各產品產量39
表4-6各時期點的產品複雜度與產量乘積41
表4-7各時期點 和 值42
表4-8 各時期點工程人員工作負荷變化比例43
表4-9 各時期點 (%)和 (%)的關係45
表4-10 在不同學習率下的各時期人力負荷值( )49
圖 目 錄
圖 1-1研究流程5
圖2-1完整層級結構圖12
圖2-2 學習曲線模式26
圖2-3 學習曲線27
圖4-1 工程部門人力負荷趨勢圖47

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