ABSTRACT This paper addresses the shortcomings of the traditional failure mode and effects analysis (FMEAs) method in the reliability analysis of industrial robots and proposes an improved comprehensive FMEA analysis method. Firstly, according to the failure characteristics of industrial robots, the new risk factors of control ( C ) and cost sensitivity ( E ) are introduced, and a six‐dimensional risk evaluation system covering severity ( S ), occurrence ( O ), detection ( D ), maintenance ( M ), C , and E is established, which enhances the applicability of the method. Secondly, during the analysis process, interval numbers are used to represent expert decision information, reducing the impact of uncertainty. These interval numbers are further transformed into cloud models to simultaneously handle the fuzziness and randomness in the evaluation. Finally, by calculating the cloud clustering coefficient between the risk priority number (RPN) value of the cloud model for each failure mode (FM) with the standard risk cloud model, a multidimensional and quantitative assessment of the comprehensive risk level is achieved. The proposed method improves the accuracy and practicality of risk level for FMs, providing effective support for the reliability analysis and maintenance decision‐making of industrial robots.
Li et al. (Thu,) studied this question.