Maintenance strategies for a queueing system with a standby equipment: An integrated approach using condition-based monitoring

This paper presents a comprehensive maintenance strategy for service systems by integrating condition-based maintenance (CBM) with queueing theory. The proposed strategy leverages real-time deterioration data to optimize server performance and reliability while balancing the costs of maintaining standby equipment and ordering new components. Our study develops an integrated maintenance model based on an M/M/1 queueing system, simulating performance degradation using condition monitoring data. This model determines the optimal reordering state for critical server equipment. Extensive numerical analyses validate its effectiveness, and a sensitivity analysis identifies key factors affecting cost and profitability. Key contributions include: (1) An integrated system model combining CBM and queueing theory to optimize maintenance strategies; (2) A computationally efficient Markov chain-based model that reduces complexity while maintaining accuracy; (3) Explicit formulas for performance metrics such as server availability, system reliability, and reorder lead time. The proposed model minimizes long-term average costs while maintaining high service availability and reliability, offering practical insights for improving maintenance efficiency across industries.