The focus of this proposal covers an innovative Model-Based Systems Engineering (MBSE) approach to Reliability, Maintainability and Availability (RMA) Management. Traditional design efforts for large complex systems rely heavily on deterministic methods to approach safety, reliability and maintainability. This results in a damage-tolerant or fail-safe design approach with frequent preventative maintenance built-in, leading to decreased performance and increased system downtime. With the evolving need for high performance and efficient systems, the application of probabilistic methods using analytical tools for predicting reliability and maintainability is the best solution for advancing the design process. The issue with most system engineer approaches for characterizing system availability is the scope of the effort resulting from the complexity of system. Therefore, MBSE offers an efficient approach to managing the many facets of Design for Availability. G2 Ops have demonstrated the potential benefits of utilizing MBSE to support Reliability Management through the automation of Failure Mode and Effect Analysis (FMEA) and System Reliability Predictions. Through this approach, it is possible to generate the necessary analyses to adequately assess the current system design and make quantifiable improvement to reliability. With the understanding of how and when components fail, MBSE can be leveraged even further to support critical maintainability decisions. With the use of maintenance modeling, component-level mean time to repair (MTTR) can be analyzed to assess the efficacy of current preventative and corrective maintenance actions. This provides critical insight into the logistics of maintaining the system and how to mitigate downtime. Through the automation of these reliability and maintainability analyses, it is possible to evaluate the systemâs operational availability. With the goal of improving system availability, G2 Ops has an integrated MBSE change management tool which allows for the analysis of the effects of prospective design changes on the predicted availability of the system. Through the automated RMA analyses provided by the MBSE environment, it is possible to achieve a higher fidelity and more efficient approach to managing system RMA performance
