Optimizing RAMS with DES Using Operational Data for Enhanced Maintenance

This paper presents a comprehensive approach to Reliability, Availability, Maintainability, and Safety (RAMS) analysis through the development of a Digital Risk Twin (DRT) and the application of Discrete Event Simulation (DES) for optimizing maintenance strategies. The research focuses on modeling the DRT of a generic aircraft, emphasizing subsystems such as the Airframe, Control System, and Powerplant. By defining functional dependencies and interactions within these subsystems, the DRT provides a detailed representation of system behavior, facilitating accurate RAMS analysis. The implementation of Reliability-Centered Maintenance (RCM) during the early stages ensures the establishment of effective maintenance strategies. These strategies are dynamically updated based on real-time operational data and environmental conditions. The integration of DES within this framework allows for the evaluation of various scenarios, providing insights into the impact of maintenance strategies on key performance indicators (KPIs) such as reliability, availability, and cost. The case study demonstrates the application of the DRT and DES to an aircraft system, highlighting the significance of breakdown and scheduled maintenance strategies. The DES model simulates the impact of different maintenance intervals on system performance, offering a robust tool for optimizing maintenance activities. The results are presented as a Pareto front, enabling users to identify the optimal balance between cost and downtime for different maintenance strategies. Future work will focus on incorporating sensitivity analysis into the DES model, allowing users to understand the interactions between input parameters and their impact on KPIs. Additionally, redefining reliability metrics, such as introducing the “Number of Unexpected Failures,” will provide more meaningful insights over extended operational periods. These enhancements will offer deeper insights into system performance, aiding in the continuous improvement of maintenance strategies. In conclusion, the model-based RAMS approach utilizing DRT and DES provides a powerful framework for enhancing system design and maintenance strategies. By continuously integrating real-time data and simulating various scenarios, this approach ensures a responsive and effective maintenance strategy, ultimately improving system reliability, availability, and cost-effectiveness throughout the lifecycle.