Risk-informed reliability assessment of nonlinear Y25 bogie suspension systems using Bayesian networks and dominant state variables

Abstract

The structural reliability of Y25 bogie suspension systems is governed by complex interactions among geometric discontinuities, material variability, manufacturing imperfections, nonlinear stiffness behaviour and assembly-related deviations. While previous studies have largely focussed on component-level stress and fatigue performance, the mechanisms by which local degradation propagates into system-level safety risks remain insufficiently addressed. This study proposes an integrated, risk-informed reliability and system-safety assessment framework that combines Ishikawa root-cause analysis, Quality Function Deployment (QFD), Design Failure Mode and Effects Analysis (DFMEA), and Bayesian Network (BN)-based probabilistic risk propagation. The Ishikawa analysis identifies 66 interacting contributors to structural degradation, highlighting the coupled influence of design, manufacturing and operational factors. QFD results reveal that spring stiffness characteristics, material fatigue resistance and geometric transition quality dominate safety-relevant system behaviour. DFMEA identifies spring seat–housing cracking, bedbox edge yielding, and fatigue crack initiation in cast-steel regions as the most critical failure modes due to their strong association with stiffness degradation and uneven load transfer. These failure mechanisms are subsequently embedded within a BN framework to quantify uncertainty propagation, identify dominant risk drivers and support time-dependent risk prioritisation across service life phases. By explicitly linking component-level degradation mechanisms to system-level instability and maintenance decision support, the proposed framework provides a structured and lifecycle-oriented methodology for reliability governance in safety-critical railway bogie suspension systems.