Model-Based Engineering/Digital Engineering (MBE/DE) and Mission Assurance of Complex NASA Systems With Federated Modeling
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systems engineering↗
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Identifying Where Mission Assurance Can Benefit from Model Based Systems Engineering
Model Based Systems Engineering (MBSE) is being introduced and used to support many aspects of the engineering of complex systems. Our focus is on space systems, with a particular interest in Mission Assurance of those systems. We seek to identify where Mission Assurance can potentially benefit when a space system is developed using an MBSE approach. To do so we consider how MBSE can help provide the evidence that Mission Assurance needs, using the recently developed NASA Reliability and Maintainability Objective Hierarchy as the exposition of those needs. We illustrate this MBSE’s potential contributions using examples drawn from our prior survey of the MBSE literature addressing space mission assurance concerns. The overall conclusion we draw from this is that there are numerous ways in which MBSE may, and in some cases already does, support Mission Assurance.
Feather, Martin S.↗
Method for Tracking and Communicating Aggregate Risk Through the Use of Model-Based Systems Engineering (MBSE) Tools
Large, complex projects can identify a significant number and variety of risks, throughout the project life cycle. These risks are analyzed, mitigated, closed or accepted as independent uncertainties. Once closed or accepted, it is easy for projects to lose awareness of their impact. In reality, each of these risks contributes some amount to the overall risk posture of the project. The ability to track and effectively communicate this aggregate risk has represented a challenge to project management. There have been previous attempts to create a schema to communicate the aggregate effect of risks, without notable success. Most of these attempts have centered on some additive metric derived from the scoring of likelihood and consequence values. This, in and of itself, is a logical approach, but all too often the scores were then aggregated to a level where all context was lost. One weakness has been a lack of attempt to create linkages or logical groups of the risks upon which useful aggregation could then occur. The overall move to model-based (systems) engineering (MBSE) has opened up a vast frontier of opportunities to better integrate all project data. MBSE provides an underlying layer that links data items to each other. Objectives link to requirements, which then link to functions, functions to physical architecture items, and so on, as far down as projects want to model. While it started with a focus on modeling requirements based on things like use cases, efforts are now underway to integrate safety and mission assurance (S&MA) information and analyses, such as risks. This effort, called Model Based Mission Assurance (MBMA), is yielding models that are more useful and are a more accurate representations of the systems. MBSE models, with this ability to link related items, provide a new means of tracking and communicating aggregate risks. In the proposed method, risks are added into the models as distinct items, having attributes that communicate a scoring derived from the likelihood and consequence values as charted on the standard NASA 5x5 risk matrix. Like earlier efforts, each box in the 5x5 has an associated scoring, which may include both a current score and potential post-mitigation/control score. The risk items are then linked to elements of the model, such as system objectives/goals, requirements, functions, or physical architecture items, with "Risk to" relationships. These risks will then be communicated by use of reports generated from the model, detailing all risks and/or hazards linked to model elements. These reports can include aggregate impacts, including a current scoring and potential future state scoring based on the planned mitigations and/or controls. These reports will show all risks, open, accepted, and closed, linked to project objectives or requirements. When run as part of an upcoming risk acceptance discussion, these reports will serve to remind the team of all previous risks that relate to the effected portion of the system. When included as part of periodic program or project reviews, risk reviews, and safety reviews, this method can improve the overall understanding of the system's true risk posture. This proposed method takes full advantage of the advances that modern modeling techniques provide, with a minimal investment of additional time. Utilizing the model environment also enables a near constant access to current state of aggregate risks.
model based mission assurance↗
System Safety Analysis of Complex NASA Systems with Model-Based Engineering
The emergence of model-based engineering is transforming design and analysis methodologies [5]. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses [1], GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System
NASA↗
Identifying Where Mission Assurance Can Benefit from Model Based Systems Engineering
No abstract available
Feather, Martin S.↗
International Cooperation on Model Based Development for Spaceflight Assurance: The Trilateral Assurance CubeSat (TACS) Test Case
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Model Based System Engineering↗
Reliability Analysis of Complex NASA Systems with Model-Based Engineering
The emergence of model-based engineering, with Model- Based Systems Engineering (MBSE) leading the way, is transforming design and analysis methodologies. The recognized benefits to systems development include moving from document-centric information systems and document-centric 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.
FMEA/FMECA↗
Reliability Analysis of Complex NASA Systems with Model Based Engineering
The emergence of model-based engineering, with Model- Based Systems Engineering (MBSE) leading the way, is transforming design and analysis methodologies. The recognized benefits to systems development include moving from document-centric information systems and document-centric 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.
Reliability prediction↗
System Safety Analysis of Complex NASA Systems with Model-Based Engineering (REV B)
The emergence of model-based engineering is transforming design and analysis methodologies. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses, GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System Safety Engineering for NASA if adequate modeling processes and environment are established.
NASA↗
NASA Quality Assurance in an MBSE world
Over the past decade or so, the emergence of Model Based Systems Engineering (MBSE) has demonstrated its desirability and value in terms of 1) being a single source of truth, 2) unambiguous definitions and relationships, and 3) after representation, the ability to explore/extract any sets of data on demand. While much work has been done in showing the value to the system engineering discipline in these areas, how does that value translate to the Safety and Mission Assurance (S&MA) world? This paper provides a vision of a very desirable future of NASA S&MA after it is fully integrated into the MBSE framework. We explore the impact and consequences of the MBSE Value items discussed above and how they impact the disciplines of quality assurance, reliability and maintainability, system safety, and software assurance. We provide insight into how the MBSE modeling tools can be used to define S&MA processes (ideally as a result of Use Case [1] elaboration of processes represented in MagicDraw®), produce S&MA products (ViewEditor output of various items), and represent S&MA disciplines (S&MA inside of MagicDraw). We also provide insight into the degree to which some elements can be directly integrated into a SysML® model and when, as often happens, an interface to some external source must be provided. The desirability of this future is part of the reason for the NASA Office of Safety and Mission Assurance’s (OSMA) recent creation of a Model Based Mission Assurance (MBMA) Program [2] and the MBMA annual workshops. We briefly summarize the efforts to date to generate S&MA Use Cases for eventual deployment into pilot and project efforts. Even simple use of the SysML modeling tools can be used to capture quality assurance tasks and integrate them with the systems engineering and produce products that are easy to use by quality practitioners that are unfamiliar with these methods. We anticipate finding opportunities to pilot and implement various Quality Assurance (QA) Use Cases in FY20. The MBMA Program is focused on implementation; the NASA Office of the Chief Engineer's Community of Practice, as well as the SmallSat communities, are very interested in the integration of S&MA. Finally, as projects move forward utilizing whatever efficiency increases they can find in a cost-constrained environment, the S&MA community cannot be caught unawares and needs to continue preparing for the ever-growing implementation of MBSE across NASA and our government and commercial partners.
Evans, John W↗
System Safety Analysis of Complex NASA Systems with Model Based Engineering
The emergence of model-based engineering is transforming design and analysis methodologies [5]. A recognized benefit of model-based engineering is the existence of a “single source of truth” about the system that becomes the authoritative source of data and information for designers, analysts, and developers. This promotes consistency and efficiency as the design emerges and can be used to further optimize the design. Integrating System Safety Engineers to the “single source of truth” will ensure that the outputs of their assessments and analyses are relevant to the design as it evolves. Use of an integrated system model enables near immediate evaluation of a design change as well as development of operational processes for risk assessment and communication. Such models can enable efficient and timely analysis of system hazards (e.g., hazard fault tree analysis and procedure simulations) and produce complete, accurate, and more consistent products (e.g., hazard reports and safety requirement evaluations). Therefore, an agency-sponsored team at Goddard Space Flight Center (GSFC) recently completed a System Safety Study of modeling and testing capabilities as part of a Model-Based Safety and Mission Assurance Initiative (MBSMAI). Using an existing model developed for reliability analyses [1], GSFC modeling and system safety experts performed system safety analysis/modeling and produced safety products. The team evaluated model-based feasibility to support System Safety Engineering, developed safety analysis modeling processes, and identified tool capability advancement/development needs. These study results indicate model-based engineering is valid and useable for System
Model Based Engineering↗
Demonstrating Assurance of Model-Based Fault Diagnosis Systems on an Operational Mission
Developers of robotic scientific and commercial spacecraft are trending towards use of onboard autonomous capabilities for responding quickly to dynamic environments and rapidly changing situations. These capabilities need to know the state of the spacecraft’s health. Model-based fault diagnosis (MBFD) is an approach to estimating health by continuously verifying accurate behavior and diagnosing off-nominal behavior. Proper functioning of MBFD depends on 1) the quality of the diagnostic system model that is analyzed and compared to commands and onboard measurements to estimate a system’s health state, and 2) the correct functionality of the diagnosis engine interrogating the model and comparing its analyses to observed system behavior. Our goal is to develop Verification and Validation (V&V) techniques for MBFD to provide future missions sufficient confidence in its functionality and performance to deploy it on the systems they develop. Our work has been focused on infusing the techniques we developed earlier to an operational mission. First, we are constructing diagnostic models of a spacecraft attitude control system and updating our diagnostic engine so they can be demonstrated aboard the Arcsecond Space Telescope Enabling Research in Astrophysics (ASTERIA) mission, an operational spacecraft for which experiments in autonomy are being planned and executed, using the V&V techniques we have previously developed to assure they are both correct and complete. Since it is nearing the end of its life, ASTERIA provides a unique opportunity to demonstrate MBFD since the monitored components are expected to fail. Our demonstration will give system developers additional confidence to make timely, informed MBFD deployment decisions. Second, we will be completing performance assessments of the diagnostic engine/diagnostic model ensemble both on the flight system and ground-based testbeds to gain confidence in MBFD’s ability to run successfully in a spacecraft’s resource-constrained environment without adversely affecting other on-board activities. Finally, we are capturing our experience in preparing this demonstration in a set of checklists and guidance documents. Current practice includes high-level institutional guidance documents and standards, but at a high level of abstraction that does not necessarily address specific MBFD concerns. The purpose of the new checklists is to provide future mission developers clear, unambiguous, procedure-oriented guidance on assuring MBFD. This paper describes our work in these areas. For the first area, we describe the diagnostic models and updated diagnostic engine that will be used for the on-board demonstration. We describe how the V&V techniques we developed earlier are used to assure model and engine correctness and completeness. For the second area, we identify the performance measurement and assessment techniques used to characterize the diagnostic engine and diagnostic models, and discuss the effect of measured performance on overall mission operation. Finally, we present the checklist and guidance documents and describe how they meet the goals of providing system developers with clear, unambiguous, procedure-oriented guidance on MBFD assurance. We show how the techniques we have developed map into those artifacts.
Nikora, Allen↗
Goal Structuring Notation in a Radiation Hardening Assurance Case for COTS-Based Spacecraft
The attached presentation is a summary of how mission assurance is supported by model-based representations of spacecraft systems that can define sub-system functionality and interfacing, reliability parameters, as well as detailing a new paradigm for assurance, a model-centric and not document-centric process.
Assurance Case↗
The NASA Commercial Crew Program (CCP) Mission Assurance Process
In 2010, NASA established the Commercial Crew Program in order to provide human access to the International Space Station and low earth orbit via the commercial (non-governmental) sector. A particular challenge to NASA has been how to determine the commercial providers transportation system complies with Programmatic safety requirements. The process used in this determination is the Safety Technical Review Board which reviews and approves provider submitted Hazard Reports. One significant product of the review is a set of hazard control verifications. In past NASA programs, 100 percent of these safety critical verifications were typically confirmed by NASA. The traditional Safety and Mission Assurance (SMA) model does not support the nature of the Commercial Crew Program. To that end, NASA SMA is implementing a Risk Based Assurance (RBA) process to determine which hazard control verifications require NASA authentication. Additionally, a Shared Assurance Model is also being developed to efficiently use the available resources to execute the verifications. This paper will describe the evolution of the CCP Mission Assurance process from the beginning of the Program to its current incarnation. Topics to be covered include a short history of the CCP; the development of the Programmatic mission assurance requirements; the current safety review process; a description of the RBA process and its products and ending with a description of the Shared Assurance Model.
Commercial Crew Program↗
Properties of a Formal Method for Prediction of Emergent Behaviors in Swarm-based Systems
Autonomous intelligent swarms of satellites are being proposed for NASA missions that have complex behaviors and interactions. The emergent properties of swarms make these missions powerful, but at the same time more difficult to design and assure that proper behaviors will emerge. This paper gives the results of research into formal methods techniques for verification and validation of NASA swarm-based missions. Multiple formal methods were evaluated to determine their effectiveness in modeling and assuring the behavior of swarms of spacecraft. The NASA ANTS mission was used as an example of swarm intelligence for which to apply the formal methods. This paper will give the evaluation of these formal methods and give partial specifications of the ANTS mission using four selected methods. We then give an evaluation of the methods and the needed properties of a formal method for effective specification and prediction of emergent behavior in swarm-based systems.
Rouff, Christopher↗
The Evolution of the NASA Commercial Crew Program Mission Assurance Process
In 2010, the National Aeronautics and Space Administration (NASA) established the Commercial Crew Program (CCP) in order to provide human access to the International Space Station and low Earth orbit via the commercial (non-governmental) sector. A particular challenge to NASA has been how to determine that the Commercial Provider's transportation system complies with programmatic safety requirements. The process used in this determination is the Safety Technical Review Board which reviews and approves provider submitted hazard reports. One significant product of the review is a set of hazard control verifications. In past NASA programs, 100% of these safety critical verifications were typically confirmed by NASA. The traditional Safety and Mission Assurance (S&MA) model does not support the nature of the CCP. To that end, NASA S&MA is implementing a Risk Based Assurance process to determine which hazard control verifications require NASA authentication. Additionally, a Shared Assurance Model is also being developed to efficiently use the available resources to execute the verifications.
Mission Assurance↗