Developing a safety management system based on functional resonance analysis method and fuzzy logic for airline ground operations

Since thousands of minor changes occur within ground operations, it is difficult to calculate how much risk these variations will pose. This study proposes a risk assessment model fed from analysis of ground operation processes using functional resonance analysis method and fuzzy logic. Functional resonance analysis method is used to detect variations in ground operation. Using the FRAM analysis, it has been revealed that how much risk the process steps described in the procedures involve. The risk score was calculated by combining the probability value obtained from the airline's database and the severity assessment of the expert group in fuzzy logic. The risk level can be monitored dynamically with the transfer of events in airline's database to the process-based risk assessment model. FRAM analysis, which is used to detect function variations before undesirable risk occurs, has brought a proactive approach to risk assessment. The process-based risk assessment model allows the creation of new safety parameter indicators to be followed in order to reduce the risk level of the function with a high-risk level. The proposed approach can be used for other operational areas in aviation as well.