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The paper focuses on the safety of railway transport and the possibility of a risk appearance in a supply chain using rail vehicles as a mode of transport. The rail transport plays a significant role in the international market for goods forwarding and transportation. In this paper, authors present own model used to predict the probability of cargo theft. In the mining and metallurgical industry, adequate protection and securing the transported cargo is extremely important. In the Silesia - industrial region of Poland, every year there are over one thousand cases of theft. The cost of such incidents is higher than one million euro per year. The railway security guards use a low-cost method to make cargo harder to steal or use the newest technology like drone monitoring system to help find the theft cargo and catch the thieves.In this paper, authors present the method which uses factors, such as the type of cargo, type of wagons, distance, delays, train speed and others, to predict the possibilities of theft during each transport case. This method can be used to develop a support system to plan the area of drone monitoring and security control of the rail line infrastructure. The presented method uses Artificial Neural Networks (ANN) as the core of the support system. The developed model can be also used to support decisions about additional cargo insurance for high risk of theft cases. This method is based on the latest data of disruptions in the supply chain, which allow appropriate response to supply chain disruptions in order to minimize losses and costs associated with losses.
Keywords: Rail transport securing, supply chain disruption, theft of the cargo, drone monitoring, security support system, artificial neural network© This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.