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

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Abstract

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.

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Data Availability

The code of the current study are available from the corresponding author on reasonable request

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Acknowledgements

The work is partially supported by National Natural Science Foundation of China (Grant No. 61973332), JSPS Invitational Fellowships for Research in Japan (Short-term)

Funding

The work was partially supported by National Natural Science Foundation of China (Grant No. 61973332), JSPS Invitational Fellowships for Research in Japan (Short-term)

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Authors and Affiliations

  1. Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Ruijie Liu & Yong Deng

  2. China Mobile Information Technology Center, Beijing, 100029, China

    Zhen Li

  3. School of Medicine, Vanderbilt University, Nashville, 37240, Tennessee, USA

    Yong Deng

Authors
  1. Ruijie Liu
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  2. Zhen Li
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  3. Yong Deng
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Contributions

All authors contributed to the study conception and design. All authors performed material preparation, data collection and analysis. Liu Ruijie wrote the first draft of the paper. All authors contributed to the revisions of the paper. All authors read and approved the final manuscript

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Correspondence to Yong Deng.

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Liu, R., Li, Z. & Deng, Y. Exponential information fractal dimension weighted risk priority number method for failure mode and effects analysis. Appl Intell 53, 25058–25069 (2023). https://doi.org/10.1007/s10489-023-04912-x

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