Economic and operational implications of corrective and preventive maintenance in stochastic multi-component systems

The design of effective maintenance policies plays a central role in determining the economic efficiency and operational reliability of complex multi-component systems subject to stochastic degradation and failure. In such systems, maintenance decisions are inherently interdependent due to visit-level setup costs, uncertainty in component deterioration, and the disruptive consequences of failure-driven interventions. This paper proposes a rigorous analytical and simulation-based framework for the systematic evaluation of maintenance strategies in multi-component systems operating over a finite planning horizon. The framework integrates discrete-time stochastic degradation modeling with explicitly defined maintenance decision rules and a cost structure that differentiates between visit-level setup costs and component-level replacement costs. System performance is assessed through Monte Carlo simulation, enabling consistent estimation of expected lifecycle maintenance cost, cost variability, intervention composition, and maintenance visit frequency. The analysis concentrates on two maintenance strategies with increasing degrees of planning structure: Policy (0), representing purely corrective maintenance, and Policy (1), corresponding to fixed-interval preventive maintenance. The numerical results demonstrate that fixed-interval preventive maintenance (Policy (1)) consistently and robustly outperforms purely corrective maintenance (Policy (0)) across all evaluated inspection intervals. Specifically, Policy (1) achieves an approximately 7% reduction in expected total maintenance cost, lowers critical failure-driven maintenance expenditures by more than 25%, and reduces both the frequency of urgent interventions and the total number of maintenance visits. In addition to improving mean economic performance, preventive maintenance substantially decreases cost variability, thereby enhancing predictability and supporting more reliable budgeting and maintenance planning. A key insight of the study is that the economic advantage of preventive maintenance is structural rather than parametric, remaining invariant with respect to inspection interval selection within the investigated range. This robustness underscores the practical relevance of fixed-interval preventive maintenance as a low-complexity yet economically effective strategy for industrial implementation. The proposed evaluation framework also contributes to more sustainable industrial operations by promoting efficient use of resources, reducing unnecessary component replacements, and supporting the development of reliable and resilient industrial systems. These improvements align with broader sustainability objectives such as SDG 9 (Industry, Innovation and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 8 (Decent Work and Economic Growth) through improved operational stability and more efficient industrial resource management.