Air Cargo Handling System Assessment Model: A Hybrid Approach Based on Reliability Theory and Fuzzy Logic

Abstract

(1) Background: This paper presents the results of a study on developing a hybrid evaluation model for air cargo handling systems, combining fuzzy logic and reliability theory. (2) Methods: The research methodology consisted of two stages: the first used reliability analysis to calculate the performance of individual processes in the cargo handling system. In contrast, the second used fuzzy logic to integrate these metrics and generate an overall system evaluation. Statistical metrics, including mean and standard deviation, were used to construct adaptable membership functions for the fuzzy logic model. (3) Results: 27 test scenarios were built, in which the impact of individual compositions of operator teams (depending on their experience) implementing individual air cargo handling processes on the final assessment of the entire system was examined. Configurations with experienced operators consistently achieved the highest performance evaluations, although the strategic integration of less experienced personnel in noncritical roles was shown to maintain system functionality. (4) Conclusions: The results confirm that the proposed model is a practical decision-support tool for air cargo terminal management. It enables precise process evaluation, supports resource optimization and increases air cargo operations’ overall reliability and efficiency.