鋼結構工程中最常發生的工地職災有墜落、物體倒塌、物體飛落與感電，也是鋼結構工程在安全管理方面最難以防範的職災風險。一般在工地安全管理無法有效落實的情況下，極易造成嚴重職災的發生。目前工地在安全管理與執行的方式，一般均侷限在現場的檢查與事後的檢討，難以對工地的安全管理有深入的瞭解，都在職災發生後才進行安全方面的檢討。為了克服此項限制，本文將鋼構工程的墜落、倒塌、飛落及感電等重大職災透過失誤樹(Fault Tree, FT)的建立，再將其關聯因子對應轉換成貝氏網路圖(Bayesian Network, BN)，並藉由專家經驗導入節點間橫向關係的連結並加入節點間的權重關係，建立鋼構工程墜落等職災風險評估的研究模式。藉此模式計算各種職災可能發生的機率及分析促使此項職災發生的各種敏感因子的影響程度。並以此分析結果探討鋼構工地安全管理執行的狀況與成效，其分析數據可提供工地做為改善安全管理與執行的具體參考，達到預防、維護及降低職災發生之機率。

Fall or tremble is the most common accident on the steel construction (SC) sites. To reduce the fall risk, current site safety management relies mostly on checklist evaluation. Nevertheless, the classical approaches ineffectively address dependencies among safety factors at different levels, which fail to provide early warning to prevent the occupational accidents. To overcome the limitations of the traditional approaches, this paper discusses the development of a safety risk assessment model for the SC projects by establishing the Bayesian Networks (BN) based on Fault Tree (FT) transformation. Through the analysis and comparison, it is found that the results of BN analysis are consistent with actual safety records; and further, It can be observed that the ranks of posterior probabilities from the BN model are also consistent with the actual accident occurred at each project site. The model provides accurately site safety management ability by calculating the probabilities of the safety risks and further analyzing accident causes through their relationships in BN. In practice, based upon the analysis of the accident risks and significant safety factors, proper preventive safety management strategies can be established to reduce the occurrences of these accidents on the SC sites.

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分析軟體
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