Reliability Analysis of Complex NASA Systems with Model-Based Engineering

Abstract

The emergence of model-based engineering, with Model-Based Systems Engineering (MBSE) leading the way, is transforming design and analysis methodologies. [7] The recognized benefits to systems development include moving from document-centric information systems and documentcentric project communication to a model-centric environment in which control of design changes in the life cycles is facilitated. In addition, a "single source of truth" about the system, that is up-to-date in all respects of the design, becomes the authoritative source of data and information about the system. This promotes consistency and efficiency in regard to integration of the system elements as the design emerges and thereby may further optimize the design. Therefore Reliability Engineers (REs) supporting NASA missions must be integrated into model-based engineering to ensure the outputs of their analyses are relevant and value-needed to the design, development, and operational processes for failure risks assessment and communication.Effective model-based Reliability must be analyst/ modeler-agnostic while still efficiently producing complete, accurate, and more consistent Reliability Artifacts (e.g., Failure Modes, Effects, and Criticality Analysis (FMECA), Limited Life Analysis (LLA), Fault Tree Analysis (FTA), Maintainability/Availability Analysis and Probabilistic Risk Assessment (PRA)) than traditional methods to allow engineers greater time for analysis, risk assessment, system behavior investigation (simulation), and risk-based project decisionmaking support. However, to achieve this, a robust and unified modeling process that includes considerations from all disciplines must be developed, implemented, and tested.In order to include Reliability, a discipline of Mission Assurance, in the development of this unified modeling process, an agency-sponsored team at Goddard Space Flight Center (GSFC) has completed the Reliability study of modeling and testing as part of the Model-Based Safety and Mission Assurance Initiative (MBSMAI). In this study, GSFC Reliability experts developed models of mission subsystems (EUROPA Propulsion, Wallops Flight Facility (WFF) Sounding Rocket Attitude Control System (ACS), & International Space Station (ISS) Evaporator) using a representative Commercial Off-The-Shelf tool, MADe (Maintenance Aware Design environment from PHM Technology-Siemens), and SysML/ MagicDraw (Systems Modeling Language (SysML) based tool from NoMagic) that was supported by Reliability plugins from Tietronix Software Inc. These models and their ability to support Reliability Analysis were then evaluated for accuracy, consistency, and efficiency to better connect and define MBSE/MBSMA modeling process best practices and modeling environment necessities that support traditional SMA analyses and milestone artifact generation so that failure risks can be assessed and communicated. Model-Based Engineering is found to be valid and useable forReliability Engineering for NASA Safety and Mission Assurance if adequate modeling processes and...

Validation of the safety requirements of the landing gear using fault tree analysis

“…On the rise are the model-based methodologies [29] that aim to achieve wide lifecycle coverage by digitally threading an array of process, modeling and simulation views into an information-loaded model of the landing gear-a digital twin [30]. The model-based systems engineering (MBSE) approach links requirements throughout the lifecycle phases, such as architecture and functional design, V&V, in-the-loop testing, and DO qualification.…”

Predictive Maintenance using Incipient Fault Detection

“…In particular, during the plant design (or redesign) phase a functional system model can be used to generate a failure diagram, namely a diagram for each component clearly summarizing all the main failure possibly involved in the component. As for this latter task, the Software MADe -Maintenance Aware Design environment, developed by PHM Technology, is perfectly suited for the purpose (Lindsey, Alimardani, & Gallo, 2020). This tool indeed provides several modules that allow users to create functional models, identify critical components, perform risk assessment, compare different maintenance strategies and carry out a sensor analysis to ensure sufficient coverage of failures.…”