Exponential information fractal dimension weighted risk priority number method for failure mode and effects analysis

As an efficient assessment technique, failure mode and effects analysis (FMEA) plays a critical role in conducting risk analyses of production and decision-making. In FMEA, the determination of the risk priority number (RPN) is the most important stage used to prioritize potential failure modes. However, the elicited RPN oftentimes contains uncertainty. Information fractal dimension is a measure of uncertainty and complexity for probability distributions. Therefore, this paper aims to propose a novel exponential information fractal dimension weighted RPN (IFDRPN). Probability distributions of assessments are provided by experts. Then, the information fractal dimension is calculated with the consideration of the uncertainty of each piece of assessment information. Furthermore, the relative importance of experts based on variable backgrounds and authorities is also taken into consideration. The corresponding FMEA is capable of measuring uncertainty and complexity in opinions for failure modes to facilitate assessment. An application of rotor blades for an aircraft turbine, along with the risk assessment in hydropower finance project, are used to demonstrate the effectiveness of the proposed FMEA approach.