善用海洋能源與資源是海島國家台灣未來的願景，例如：離岸風電廠、深層海水等，而完善的海事工程技術更是這類開發的基石。面對艱險的海洋環境，各類海事工程的風險非常高，如何在現有工程技術，加強海事工程風險管控，除了確保工程計畫的品質，並可提升台灣海事工程的技術層次，發展具國際競爭力的海事工程產業。
海事工程有其標準施工作業流程，但是減少工程風險則多有賴於專家經驗與知識，因此當缺少經驗豐富的專家、或只有口語敘述的質性經驗時，如何建立明確的工程風險因子結構，並量化與管控風險因子，實屬重要之課題。本研究將以海事工程中的海底管線鋪設為案例，彙整、分析國內外文獻，並與海事工程公司合作，進行專家訪談，確認海底鋪管之風險因子，接著應用明示結構法，找出各因子的因果網路圖，再將專家經驗轉換成前置、條件機率，完成貝氏網路之建構。研究結果顯示出使用貝氏網路進行預測時，前期作業對於後期作業必定產生影響，進行事後推論時，可找出前期作業失誤因子。

Taiwan, as an island country, should place future aspiration on the usages of ocean energy and marine resources, such as offshore wind power and deep ocean water. The sound development of marine services relies on a strong industry of maritime engineering. The perilous marine environment has posed the highest risk for all maritime civil engineering activities. It is therefore imperative to restrain the risk associated with current maritime work, other than just engineering technique itself. By doing so, the quality of maritime work can be assured, and as the improvement of overall engineering capability, Taiwan can compete worldwide in the maritime engineering industry.
Maritime works have developed their own standard construction procedures. To mitigate risk of maritime works depend mainly on the domain experts’ experience and know-how. However, problems appear when less experienced experts are available, or qualitative experience exists in a narrative form. It is therefore important to structure clearly an engineering risk factor relation, and quantify and control these risk factors. The proposed study will first collect and review related literatures, and then interview an expert from the designate maritime service company to establish the risk factors associated with offshore piping. Eventually a complete Bayesian network (BN) was formulated based on the cause-effect diagram, using Interpretive Structural Modeling (ISM), and experts’ experience was transformed into a set of prior and conditional probability to be embedded in the BN. The BN can clearly show that certain earlier operational factors affect final operational process deeply. Besides, the backward reasoning using the BN is possible to identify the factors causing a project failure.

目錄 I
圖目錄 II
表目錄 IV
第一章、緒論 1
1.1 研究動機與目的 1
1.2 研究流程 2
1.3 研究範圍 4
第二章、文獻回顧 5
2.1 風險定義 5
2.2 明示結構法 6
2.3 貝氏網路 7
2.4 GeNIe 2.0 介紹 12
第三章、研究方法 13
3.1 海底管線鋪設工程因子評選 13
3.2 建立ISM層級架構 15
3.3 建立貝氏網路 29
第四章、研究成果 37
4.1 網路模型測試 37
4.2 情境分析 55
4.3 結果總結 59
第五章 結論與建議 61
5.1 研究結論 61
5.2 建議 61
參考文獻 63
附錄一、條件機率表(專家一) 67
附錄二、條件機率表(專家二) 70
附錄三、條件機率表(平均整理) 73
意見與回覆 76

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