Failure mode and effects analysis (FMEA) is a systematic reliability analysis technique used in various industries to identify, mitigate and eliminate failure risks. However, the classical FMEA paradigm has limitations when managing complex and uncertain environments. Complex decisions usually involve the participation of multiple decision makers (DMs), and differences between individual assessments are almost inevitable. Reducing differences requires some DMs to adjust their assessments, which implies cost and resource consumption. This chapter proposes a novel consensus-based FMEA model for risk assessment, which combines minimum-cost conflict risk mitigation (MCCRM) and probabilistic linguistic information. First, probabilistic linguistic term sets are used to describe the risk assessments in response to uncertainty and fuzziness. The MCCRM process is then integrated into FMEA to reduce the differences among individual risk assessments at the minimum adjustment cost. The process incorporates a new consensus constraint, called the explicit feedback constraint, into classical MCCRM to ensure the movement of individuals to the group assessment. On this basis, two types of enhanced MCCRM models are proposed, which concretize adjustment amounts and overcome the limitation of over-adjustment caused by classical MCCRM. Finally, the feasibility of the proposed model is illustrated by taking the risk assessment of global production site selection as a case.