earticle

영어

In this study, a fuzzy inference method is applied to improve the result of accident risk when an uncertainty is involved in data. In Korea, ports are taking care of 99% of the total volume of international trade, where accidents related to cargoes loading/unloading activities happen. Though the accident rate is lower than other logistics industries, the consequence of any accident and its negative after effect often cause severe results in trade transactions at the national level. The risk analysis is a method used in many fields to calculate the level of risk using accident probability(frequency) and corresponding consequence(damage) when an accident occurs. And the fuzzy inference technique is normally used to inference the result when given data are not enough to employ for the analysis. Since the accident data for port related activities do not occur frequently, there exists uncertainty in the resulting risk level. Therefore, we combine a risk analysis technique, i.e. risk matrix with fuzzy inference to calculate the risk level of port accident using real accident data over the 5 year period(2009-2013). The results are following: for accident types, External Truck Damage(ETD), Container & Cargo Damage for Quay operation(CCDQ), Yard Equipment Damage(YED) are the riskiest accidents and main causes of accidents are mishandling of equipment, equipment malfunction, and collision between spreader and container. We calculated the accident risk levels of each risk factor based upon which more practical accident mitigation measures could be applied to reduce the overall risk level. Since most of the accidents results from diverse human factors, future research should be focused on the detailed classification and analysis of them. The primary purpose of risk analysis is to find the potential risky factors, calculate the risk, and establish proper risk reduction plans and implementation of them, industry-specific risk assessment techniques should be developed in more proper way. Also, for each risk mitigation measure, a necessary way to judge the effect of it, i.e., a cost-benefit analysis should be implemented in decision-making process.