Condition-based maintenance optimization for two-component series systems with interactive degradation

Two-component series systems with interactive degradation, such as twin-gear transmission systems, are commonly encountered in practice. Prompt maintenance of these parts is crucial to guarantee the dependable and economical functioning of such systems. Thus, an optimized inspection and Condition-Based Maintenance (CBM) strategy is devised for these systems. The mutual degradation of the two components is modeled by accounting for both the stochastic degradation of each individual component and their reciprocal influences. Leveraging the interactive degradation models, the system state transition probability is computed. The calculation of system downtime cost involves an analytical formulation of the system’s remaining service life, considering the interdependent degradation among components. Condition-Based Maintenance (CBM) optimization is structured as a Markov Decision Process (MDP), aiming to identify optimal maintenance m easures and inspection intervals to cut down the system’s long-term overall operating expenses. To verify the effectiveness of the proposed CBM strategy, a numerical investigation is conducted. The interactive degradation model innovatively quantifies th e bidirectional coupling effect of component degradation, offering an accurate modeling tool to unveil practical phenomena like “mild wear of a single component triggering chain degradation of the system” in twin-gear transmission systems. This method notably boosts the adaptability of maintenance strategies to real-world engineering scenarios.