A formal method for analysing and assessing operational risk in supply chains

This paper formalises an objective method to identify and assess operational risk in supply chains. The proposed approach exploits the analogy among logistics networks and dynamical systems. In particular, risky events identification is based on the analysis of the coverability graph of the timed attributed Petri net describing the analysed supply chain, whereas risk assessment is done by building the simulation model of the studied logistic network, experimenting on it and applying ANOVA to analyse the results and evaluating the importance among the risky events previously figured out. The method has been applied to an example case represented by a single‐item, three‐stage supply chain.