Reconfigurable manufacturing systems (RMS) are designed to enhance adaptability in response to individualized customer demands, offering a promising pathway toward mass personalization. However, like traditional manufacturing systems, RMSs are susceptible to machine or module failures, which can hinder specific functionalities across interconnected machines and disrupt production flow. With the advancement of smart manufacturing technologies—such as embedded sensing and the Industrial Internet of Things—it is increasingly feasible to monitor machine conditions and implement preventive maintenance strategies to mitigate the risk of unexpected downtime. However, miscoordination between maintenance and reconfiguration activities can undermine system responsiveness and compromise its reconfigurability. In this context, striking an optimal balance between system adaptability and healthiness in delivering production demands remains a critical yet underexplored challenge. This chapter proposes a degradation-aware RMS decision-making model to optimally determine and adjust operational actions in real-time considering demand fulfillment, maintenance cost, and system health.