Process failure mode and effects analysis for rail transit vehicles

Customized small-batch production of rail transit vehicles involves complex processes with uncertain quality risks, rendering traditional Risk Priority Number (RPN) methods insufficient for identifying key failure modes. This study proposes a Fuzzy Risk Priority Number (FRPN) model that integrates fuzzy theory, grey relational analysis, and evidence theory to improve the reliability of process risk assessment. Empirical results from welding process analysis show that the method effectively identifies high-severity, low-probability defects such as weld cracks. Compared with the traditional RPN approach, the FRPN model improved defect prioritization and led to a 15% reduction in crack occurrence and a 10% improvement in production efficiency. The proposed method enhances risk differentiation under uncertainty and provides practical support for quality control in rail vehicle manufacturing.