A Calibrated Linguistic Semantic Based on Group Consensus Decision Making for FMEA of Industrial Internet Platform

Failure mode and effects analysis (FMEA) is a powerful risk management tool and engineering technique for eliminating potential failures. This paper aims to improve FMEA by introducing the calibrated linguistic semantic (CIS) and a consensus reaching process with minimum adjustment cost. CIS can effectively solve the problem that different individuals may have different understandings of the same term, and the consensus reaching process can reduce the potential inconsistency and conflict to make the result of rank more accurate and convincing. A novel criteria weight allocation method based on the performance of alternatives is used to obtain the relative weights of risk factors (RF), which is not only based on the function framework but also can obtain the relative weight of RFs through the evaluation matrix directly. Then, the proposed FMEA framework is applied to the industrial internet platform. Finally, the comparisons between the proposed and other methods are presented to demonstrate the effectiveness and advantages of the new method.