## 4 Discussion  
This study discovered that the MV Milano Bridge accident, which was caused by factors related to human error, is still a major concern for marine safety management and large ship berthing operations, even though the technical causes are decreasing with the introduction of ship safety management and technological development. The results obtained by analyzing the MV Milano Bridge accident using FRAM identified the importance of technical, human, and organizational factors in marine accidents and linked them with the accident results. It can be observed that factors related to human error, based on marine accident risk assessment, have an important impact on large container ships in ports. This study differentiates itself from the existing academic research on marine accidents by presenting a novel approach to systematically analyze accidents from a preventive perspective, aiming to reduce human error and enhance marine safety in pilotage and port operations. Thus, this study aimed to lay the foundation for the analysis of system causes from a preventive perspective to reduce human error and prevent marine accidents, including pilotage and ports, in the event of future marine accidents at ports. For this purpose, a causality system was analyzed by classifying various complex factors using port contact accidents that occurred during the entry of the MV Milano Bridge into Busan New Port as a reference. The summary for RQ 1 is as follows. In large-scale marine accidents, complex cause-and-effect relationships may be entangled in addition to simple causes. In this study, to systematically analyze the causal relationship by considering the MV Milano Bridge harbor collision accident, which is a large-scale marine accident, complex organization-technology, people-technology, and organization-human relationships related to this accident were logically explored through FRAM. For a logical analysis through FRAM, the factors of the MV Milano Bridge accident were divided into functions, and the six aspects (time, input, precondition, resource, outcome, and control) of these individual functions were analyzed in detail. The causal relationship of each function based on these six aspects was derived using the FRAM model. However, when deriving a causal relationship using the FRAM model, a linear connection is suggested, and an additional derivation of the importance of each factor is required. The summary of RQ 2 is as follows. In this study, a quantitative evaluation was performed to determine the importance of the factors of the MV Milano Bridge accident derived through the FRAM model and to suggest improvement measures accordingly. For a quantitative evaluation, three factors were derived, and cumulative multiplication was performed for each function. The evaluation was performed by defining the three factors as the aspect activation factors, based on text mining, and the connectivity of functions. Through the application of FRAM, the causes of the Milan bridge accident were identified as a complex interplay of several factors, including not only human errors of the captain and the pilot, but also technological factors that contributed to their errors. The functions and improvement measures derived as important causes of accidents are summarized as follows. To derive the accident priority for each function (\(F_{pi}\)), such as the technical factors identified through FRAM, the importance of each function related to accidents is based on the activation of aspects of each function, frequency analysis of keywords related to accident analysis, and the in-out connectivity of functions. This was quantitatively evaluated using the cumulative multiplication method. As a result of the evaluation, Function 15 (inadequate ballast) was \(F_{pi}\) 12.5, Function 18 (insufficient communication) was \(F_{pi}\) 12.6, Function 19 (fast maneuvering speed) was \(F_{pi}\) 28.8, Function 21 (insufficient tug assistance) was \(F_{pi}\) 22.8, and Function 27 (large alteration of courses) was \(F_{pi}\) 38.4.