OSMA’s Emerging Digital “Assurance Case” Framework
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The evolution from “document-centric” to “data-centric” and “model-centric” information leveraging structured data and model-based approaches is at the heart of digital engineering transformational efforts underway across industry and government. It is these approaches that pave the way for data lakes, Authoritative Sources of Truth (ASOTs), and systems- of-systems interoperability and the corresponding transformational benefits thereof. Such benefits include increased data availability, data access equity, data traceability, real-time analytics, batch analytics, and (most importantly) acceleration of the time-to-value and time-to-insights associated with engineering products and analyses. The longer-term benefits of reusability, customization and traceability are even more promising. For Safety and Mission Assurance (SMA), and Mission Success (SMS) activities; realization of such benefits is essential to provide engineers and analysts alike vital information when needed to support critical decision making throughout the entire life cycle. The SMA community often operate in parallel with engineering activities, for which information exchange with relevant context is paramount. Far too often, such information lags key decision points and/or is absent of the robust, integrated, knowledge needed, given inherent barriers associated with traditional document-centric means to data sharing, analysis, and reporting. This paper provides an overview of how NASA’s Office of Safety and Mission Assurance (OSMA) is evolving its policies, standards, guidance, and training to transform to eliminate such barriers, thus realizing the benefits emerging in this new digital era. A roadmap for achieving this digital future is presented along with key building blocks involving use and implementation of concepts such as: Objectives-Hierarchies, Objective-Driven Requirements, Accepted Standards, Safety and Assurance Cases, data digitization (i.e., ontologies, structured data, and model-centric data), FAIR (Findable, Accessible, Interoperable, & Reusable) and/or FAIRUST (Findable, Accessible, Interoperable, Reusable, Understandable, Secure, and Trusted) principles [1]. This paper also describes how OSMA, leveraging the Agency’s overall commitment to Digital Transformation (DT), is using the power of Policy, “Digital” Domain representation, Product Evolution, and Community Outreach and Engagement as part of a strategic vision and roadmap to evolve and transform its SMA organizations to become better able to serve its stakeholders and customers. Future publications will elaborate on these building blocks and deeper concepts.
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NASA Ames Research Center (ARC) has engaged Military Branches, the Department of Defense, and other Government Agencies in successful partnerships to design, develop, deliver and support various space effects capabilities and space vehicles on timeline of need. Contracts with Industry are in place to execute operational and enabler missions using physical and informational infrastructures including Responsive Manufacturing capabilities and Digital Assurance. The intent is to establish a secure, web-enabled "store front" for ordering and delivering any capabilities required as defined by the users and directed by NASA ARC and Partner Organizations. The capabilities are envisioned to cover a broad range and include 6U CubeSats, 50-100 kg Space Vehicles, Modular Space Vehicle architecture variations, as well as rapid payload integration on various Bus options. The paper will discuss the efforts underway to demonstrate autonomous manufacturing of low-volume, high-value assets, to validate the ability of autonomous digital techniques to provide Mission Assurance, and to demonstrate cost savings through the identification, characterization, and utilization of Responsive Space components. The culmination of this effort will be the integration of several 6U satellites and their launch in 2016.
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This viewgraph presentation explains the USGS plan for monitoring and assuring the quality of digital aerial data. The contents include: 1) History of USGS Aerial Imaging Involvement; 2) USGS Research and Results; 3) Outline of USGS Quality Assurance Plan; 4) Other areas of Interest; and 5) Summary
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The integrated application of reliability, failure effects and system simulator methods in establishing the airworthiness of a flight critical digital flight control system (DFCS) is demonstrated. The emphasis was on the mutual reinforcement of the methods in demonstrating the system safety.
Discussed are hardness assurance and testing techniques to test and evaluate total dose radiation degradation of high resolution A/D converters. Because high-speed, high-resolution converters are critical parts in a digital signal processing or data acquisition system, the evaluation of performance in the early design phase is very important. Converters from three manufacturers are evaluated.
On-line digital computer system for real time acquisition and processing of data at Materials Analysis Section of Quality and Reliability Assurance Laboratory
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Qualification considerations for assuring the safety of a life-critical digital flight control system include four major areas: systems interactions, verification, validation, and configuration control. The AFTI/F-16 design, development, and qualification illustrate these considerations. In this paper, qualification concepts, procedures, and methodologies are discussed and illustrated through specific examples.
This submission includes 11 presentations prepared by NASA for the Trilateral Safety & Mission Assurance (SMA) Conference from June 24-26th at the ESA Centre for Earth Observation. These presentations encompass various safety & mission assurance topics focused on the conference themes of lunar exploration, space sustainability, new commercial partners & challenges, digital engineering, and the assurance of new technologies. These presentations will be shared amongst an international community of SMA practitioners & leadership to promote mutual dialogue on initiatives & challenges of SMA in an evolving spaceflight field.
Error protection assurance in the reliability of digital data communications is discussed. The need for error protection on the space shuttle data bus system has been recognized and specified as a hardware requirement. The error protection techniques of particular concern are those designed into the Shuttle Main Engine Interface (MEI) and the Orbiter Multiplex Interface Adapter (MIA). The techniques and circuit design details proposed for these hardware are analyzed in this report to determine their error protection capability. The capability is calculated in terms of the probability of an undetected word error. Calculated results are reported for a noise environment that ranges from the nominal noise level stated in the hardware specifications to burst levels which may occur in extreme or anomalous conditions.
Instrument reads tip temperature and contact potential in seconds. Tinned soldering tip touched to temperature sensitive button for 4 seconds and to voltage probe for 1 to 3 seconds. Tip temperature and voltage appear on digital displays. Instrument quickly gives assurance conditions are correct for reliable soldering.
This report validates and documents the detailed features and practical application of the framework for software intensive digital systems risk assessment and risk-informed safety assurance presented in the NASA PRA Procedures Guide for Managers and Practitioner. This framework, called herein the "Context-based Software Risk Model" (CSRM), enables the assessment of the contribution of software and software-intensive digital systems to overall system risk, in a manner which is entirely compatible and integrated with the format of a "standard" Probabilistic Risk Assessment (PRA), as currently documented and applied for NASA missions and applications. The CSRM also provides a risk-informed path and criteria for conducting organized and systematic digital system and software testing so that, within this risk-informed paradigm, the achievement of a quantitatively defined level of safety and mission success assurance may be targeted and demonstrated. The framework is based on the concept of context-dependent software risk scenarios and on the modeling of such scenarios via the use of traditional PRA techniques - i.e., event trees and fault trees - in combination with more advanced modeling devices such as the Dynamic Flowgraph Methodology (DFM) or other dynamic logic-modeling representations. The scenarios can be synthesized and quantified in a conditional logic and probabilistic formulation. The application of the CSRM method documented in this report refers to the MiniAERCam system designed and developed by the NASA Johnson Space Center.
Provide an overview of OSMA related activities to help instantiate both Safety & Mission Assurance (SMA) and Reliability & Maintainability (R&M) activities as part of a Digital Engineering Eco System.
Formal specification combined with mechanical verification is a promising approach for achieving the extremely high levels of assurance required of safety-critical digital systems. However, many questions remain regarding their use in practice: Can these techniques scale up to industrial systems, where are they likely to be useful, and how should industry go about incorporating them into practice? This report discusses a project undertaken to answer some of these questions, the formal verification of the AAMPS microprocessor. This project consisted of formally specifying in the PVS language a rockwell proprietary microprocessor at both the instruction-set and register-transfer levels and using the PVS theorem prover to show that the microcode correctly implemented the instruction-level specification for a representative subset of instructions. Notable aspects of this project include the use of a formal specification language by practicing hardware and software engineers, the integration of traditional inspections with formal specifications, and the use of a mechanical theorem prover to verify a portion of a commercial, pipelined microprocessor that was not explicitly designed for formal verification.