「人為因素分析與歸類系統」根據 James Reason (1990) 的「顯性與隱性的人為失誤」理論模型，所發展出架構完整且包含組織管理層級到個別的操作者的飛安事件之人為因素歸類系統（Shappell & Wiegmann, 2003）。從過去所統計的海事事件中發現，在台灣無論是商船或軍艦均有將近八成的事故是由人為因素所造成。96年海軍海事及危安事件彙編亦指出，所有事故的失事來源以人為因素佔了77.4％為主要肇事原因，而環境因素佔14％次之，機械因素則佔8.6％。本研究以海軍自88年至96年間的131件失事事件為樣本，運用HFACS模式分析後發現，每一較高層級子項目，多數可測得較低層級子項目（τ值，p <.05）之預測效果，程度均介於3％至16％之間；另以勝算比（odds ratio）分析，亦發現高層級子項目出現比高層級子項目不出現，對低層級子項目出現的機率介於.37至34.57倍之間，本研究結果檢驗出上一層級人為失誤引發下一層級海事事件的預測效果，以提供防範與精進之參考。

Based upon Reason’s model (1990) of human errors in which active failures and latent failures are characterized as inadequacies which might lie dormant within a system for a long time and are only triggered when combined with other factors to breach the system’s defenses, the Human Factors Analysis and Classification System (HFACS) was developed as an analytical framework for the investigation of the role of human factors in aviation accidents (Shappell ＆ Wiegmann, 2003). According to previous studies of maritime mishaps, more than 80 percent of the accidents were caused by human errors on both civil or military ship. In The Statistic of Maritime Mishaps, 77.4% of the mishaps were caused by human errors; though only 14 % were caused by environmental conditions and 8.6% by mechanic errors (2007). This study is aimed at providing a future reference for identifying the cause of human errors by analyzing the cause and process of mishaps. This research analyzed in total 131 accident reports between 1999 and 2007. The categories at higher levels have predicted power between 3% and 16 % toward the categories at lower levels. The values of odds ratio were found between .37 and 34.57. The results might provide maritime authorities for improving maritime safety by defining the elements of higher level human errors that cause low level maritime affairs.