Mathematical Evaluation of Operational Reliability Indicators of Overhead Bridge Cranes Based on Defect Severity, Inspection Data, and Remaining Useful Life

Source abstract

Operational reliability assessment for overhead bridge cranes remains fragmented across structural reliability analysis, non-destructive inspection, condition monitoring, and remaining useful life prediction. Existing studies usually treat these directions separately: accident reliability is evaluated through fault-tree, Markov, and fuzzy Bayesian models; girder failure is assessed probabilistically under uncertain design parameters; structural integrity is examined through finite-element analysis and non-destructive testing; and fatigue or bearing degradation is predicted through damage accumulation and stochastic prognostic models. This paper proposes a unified mathematical framework for evaluating operational reliability indicators of overhead bridge cranes by combining three information streams: normalized defect severity, inspection evidence quality, and predicted remaining useful life. The framework defines component-level and system-level reliability indicators, introduces a confidence-adjusted defect severity index, applies Bayesian updating for new inspection cycles, and links degradation state to time-dependent hazard and reliability functions. The proposed indicators are designed to support maintenance prioritization, inspection scheduling, and continued-operation decisions for critical crane subsystems, such as girders, end carriages, hoisting mechanisms, wire ropes, brakes, wheels, and gearboxes. Although the study is methodological rather than experimental, it is structured for direct implementation using routine inspection sheets, non-destructive testing results, sensor-based monitoring data, and maintenance histories. The main contribution is an integrated decision-support formulation that preserves the mechanical meaning of defects while providing a probabilistic interpretation of operational reliability.