Assessment of supply chain risks using interval type-2 fuzzy sets

Supply chain risk management is a frequently addressed topic in supply chain management research and can be defined as the identification, assessment and management of risks in the supply chain. The risks in the supply chain are caused by various sources, e.g. environmental, supplier, demand and operational risks. The assessment of these risks generally requires dealing with vague and imprecise information as well as highly subjective judgments of a group of experts. A number of precision-based methods addressing this issue have been suggested in the literature. However, these studies entirely or partly have ignored certain sources of uncertainties, especially subjectivity and variations among expert judgments. This paper proposes an interval type-2 fuzzy FMEA approach that effectively models the supply chain risk assessment process. The approach captures at least two types of uncertainties associated with judgments elicited from a group of experts: intra-personal uncertainty and inter-personal uncertainty. To demonstrate the proposed approach, an illustrative example is presented.