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The problem of classification of risk factors in an uncertain environment is part of the risk management problem, which has a critical effect on the competitive advantage of production supply chain. The severities of consequences, their relative importance, and the frequency of occurrence of risk factors are defined by risk management team, depending on their experience and the results of good practice. Fuzzy rating of the severities of consequences and the frequency of occurrence of risk factors are described by linguistic expressions, which are modeled by triangular fuzzy numbers. The risk values, obtained by the materialization of the identified risk factors, are given precisely with the usage of fuzzy algebra rules. The classification criterion is defined as the distance between current risk value and extreme risk values. The proposed model enables determination of the priorities of risk factors. It is illustrated by an example with real-life data from a production supply chain in auto industry

ABC Classification of Risk Factors in Production Supply Chains with Uncertain Data