A Novel FMEA Method Considering Dynamic Weights and Its Application to CNC Machine Tools

ABSTRACT Failure Mode and Effects Analysis (FMEA) is a widely used tool in reliability engineering for risk assessment and failure prevention. However, its effectiveness is often hampered by the inherent subjectivity of expert judgments and the dynamic nature of risk factors, whose weights may evolve over time, leading to instability in risk prioritization. To address these challenges, this paper proposes a novel dynamic FMEA framework integrating q‐rung orthopair fuzzy sets (q‐ROFs) with the Muirhead mean (MM) operator. We introduce the dynamic q‐rung orthopair fuzzy Muirhead mean (Dq‐ROFMM) and weighted Muirhead mean (Dq‐ROFWMM) operators, which effectively aggregate multiperiod evaluation data and capture interrelationships among risk criteria. Additionally, a new score function is developed to enhance the discrimination capability between q‐rung orthopair fuzzy number (q‐ROFN). The proposed method is applied to a five‐axis gantry CNC machine tool, where it identifies the tool magazine system as the most critical subsystem, followed by the spindle and feed system—a finding consistent with empirical failure data. Comparative studies demonstrate that the framework offers improved stability, generality, and validity over existing FMEA approaches, providing a more robust and flexible tool for reliability design in complex mechanical systems.