Multidisciplinary Analysis of Fault Management Design for System Autonomy and Resilience

A major step in fulfilling NASArsquo;s technology needs to increase system autonomy and resilience is to connect fault management (FM)/System Health Management (SHM) to systems engineering (SE) and operations. There are recent trends to improve SE through the use of models to create model-based SE (MBSE) and connect FM to SE and operations. One such approach for performing a rigorous SE is the Goal-Function Tree (GFT) representation using Systems Modeling Language (SysML) that was developed at NASA JPL and MSFC.nbsp;Despite their inherently close relationship to SE in practice, SHM/FM practices have remained disjoint and not tightly integrated with SE. Historically, SHM has been designed into the system only after the nominal system is designed, which essentially makes it a band-aid of the problems without consideration of how these might have been prevented or mitigated. Between SE and SHM/FM, separate sets of Subject Matter Experts (SMEs), knowledge repositories, modeling methodologies and analyses processes with non-relatable results are typical. This lends itself to a large technology and knowledge gap between the two sets of practices that result in significant inefficiencies throughout the life cycle, from design through verification and validation (Vamp;V) through operations.Qualtech Systems, Inc. (QSI) plans to integrate TEAMSreg; analytic capabilities with GFT to provide a multidisciplinary solution that connects an important SE approach with a tool that provides analytic capabilities for FM design and operations. It intends to integrate SHM/FM directly within SE from the beginning of a project, thereby suitable for FM of future spacecraft. This effort: (1) performs FM design analysis of a system design modeled in GFT, (2) enables FM design to be evaluated in an operational context by performing SHM functions, (3) supports Trade Studies to evaluate merits of FM architecture; and (4) enables ldquo;Systemrdquo; level assessment and visualization of FM qualities modeled in GFT.