A Model-Based RAMS Estimation Methodology for Innovative Aircraft on-board Systems supporting MDO Applications
The reduction of aircraft operating costs is one of the most important objectives addressed by aeronautical manufactures and research centers in the last decades. In order to reach this objective, one of the current ways is to develop innovative on-board system architectures, which can bring to lower fuel and maintenance costs. The development and optimization of these new aircraft on-board systems can be addressed through a Multidisciplinary Design Optimization (MDO) approach, which involves different disciplines. One relevant discipline in this MDO problem is Reliability, Availability, Maintainability and Safety (RAMS), which allows the assessment of the reliability and safety of aircraft systems.Indeed the development of innovative systems cannot comply with only performance requirements, but also with reliability and safety constraints. Therefore, the RAMS discipline plays an important role in the development of innovative on-board systems. In the last years, different RAMS models and methods have been defined, considering both conventional and innovative architectures. However, most of them rely on a document-based approach, which makes difficult and time consuming the use of information gained through their analysis to improve system architectures. On the contrary, a model-based approach would make easier and more accessible the study of systems reliability and safety, as explained in several studies.Model Based Systems Engineering (MBSE) is an emerging approach that is mainly used for the design of complex systems. However, only a few studies propose this approach for the evaluation of system safety and reliability. The aim of this paper is therefore to propose a MBSE approach for model-based RAMS evaluations. The paper demonstrates that RAMS models can be developed to quickly and more effectively assess the reliability and safety of conventional and innovative on-board system architectures.In addition, further activities for the integration of the model-based RAMS methodology within MDO processes are described in the paper.