Model Based Mission Assurance: NASA's Assurance Future

Model Based Systems Engineering (MBSE) is seeing increased application in planning and design of NASAs missions. This suggests the question: what will be the corresponding practice of Model Based Mission Assurance (MBMA)? Contemporaneously, NASAs Office of Safety and Mission Assurance (OSMA) is evaluating a new objectives based approach to standards to ensure that the Safety and Mission Assurance disciplines and programs are addressing the challenges of NASAs changing missions, acquisition and engineering practices, and technology. MBSE is a prominent example of a changing engineering practice. We use NASAs objectives-based strategy for Reliability and Maintainability as a means to examine how MBSE will affect assurance. We surveyed MBSE literature to look specifically for these affects, and find a variety of them discussed (some are anticipated, some are reported from applications to date). Predominantly these apply to the early stages of design, although there are also extrapolations of how MBSE practices will have benefits for testing phases. As the effort to develop MBMA continues, it will need to clearly and unambiguously establish the roles of uncertainty and risk in the system model. This will enable a variety of uncertainty-based analyses to be performed much more rapidly than ever before and has the promise to increase the integration of CRM (Continuous Risk Management) and PRA (Probabilistic Risk Analyses) even more fully into the project development life cycle. Various views and viewpoints will be required for assurance disciplines, and an over-arching viewpoint will then be able to more completely characterize the state of the project/program as well as (possibly) enabling the safety case approach for overall risk awareness and communication

Model Based Mission Assurance in a Model Based Systems Engineering (MBSE) Framework: State-of-the-Art Assessment

This report explores the current state of the art of Safety and Mission Assurance (S&MA) in projects that have shifted towards Model Based Systems Engineering (MBSE). Its goal is to provide insight into how NASA's Office of Safety and Mission Assurance (OSMA) should respond to this shift. In MBSE, systems engineering information is organized and represented in models: rigorous computer-based representations, which collectively make many activities easier to perform, less error prone, and scalable. S&MA practices must shift accordingly. The "Objective Structure Hierarchies" recently developed by OSMA provide the framework for understanding this shift. Although the objectives themselves will remain constant, S&MA practices (activities, processes, tools) to achieve them are subject to change. This report presents insights derived from literature studies and interviews. The literature studies gleaned assurance implications from reports of space-related applications of MBSE. The interviews with knowledgeable S&MA and MBSE personnel discovered concerns and ideas for how assurance may adapt. Preliminary findings and observations are presented on the state of practice of S&MA with respect to MBSE, how it is already changing, and how it is likely to change further. Finally, recommendations are provided on how to foster the evolution of S&MA to best fit with MBSE

Phase 2: Investigation of Leading Indicators for Systems Engineering Effectiveness in Model-Centric Programs

Acquisition Research Program Sponsored Report SeriesSponsored Acquisition Research & Technical ReportsThis technical report summarizes the work conducted by Massachusetts Institute of Technology under contract award HQ0034-20-1-0008 during the performance period May 22, 2020 – July 31, 2021. Digital engineering transformation changes the practice of systems engineering, and drives the need to re-examine how engineering effectiveness is measured and assessed. Early engineering metrics were primarily lagging measures. More recently leading indicators have emerged that draw on trend information to allow for more predictive analysis of technical and programmatic performance of the engineering effort. By analyzing trends (e.g., requirements volatility) in context of the program’s environment and known factors, predictions can be forecast on the outcomes of certain activities (e.g., probability of successfully passing a milestone review), thereby enabling preventative or corrective action during the program. Augmenting a companion research study under contract HQ0034-19-1-0002 on adapting and extending existing systems engineering leading indicators, this study takes a future orientation. This report discusses how base measures can be extracted from a digital system model and composed as leading indicators. An illustrative case is used to identify how the desired base measures could be obtained directly from a model-based toolset. The importance of visualization and interactivity for future leading indicators is discussed, especially the potential role of visual analytics and interactive dashboards. Applicability of leading edge technologies (automated collection, visual analytics, augmented intelligence, etc.) are considered as advanced mechanisms for collecting and synthesizing measurement data from digital artifacts. This research aims to provide insights for the art of the possible for future systems engineering leading indicators and their use in decision-making on model-centric programs. Several recommendations for future research are proposed extending from the study.Approved for public release; distribution is unlimited.Approved for public release; distribution is unlimited

Applying model-based systems engineering to architecture optimization and selection during system acquisition

2018 Fall.Includes bibliographical references.The architecture selection process early in a major system acquisition is a critical step in determining the overall affordability and technical performance success of a program. There are recognized deficiencies that frequently occur in this step such as poor transparency into the final selection decision and excessive focus on lowest cost, which is not necessarily the best value for all of the stakeholders. This research investigates improvements to the architecture selection process by integrating Model-Based Systems Engineering (MBSE) techniques, enforcing rigorous, quantitative evaluation metrics with a corresponding understanding of uncertainties, and stakeholder feedback in order to generate an architecture that is more optimized and trusted to provide better value for the stakeholders. Three case studies were analyzed to demonstrate this proposed process. The first focused on a satellite communications System of Systems (SoS) acquisition to demonstrate the overall feasibility and applicability of the process. The second investigated an electro-optical remote sensing satellite system to compare this proposed process to a current architecture selection process typified by the United States Department of Defense (U.S. DoD) Analysis of Alternatives (AoA). The third case study analyzed the evaluation of a service-oriented architecture (SOA) providing satellite command and control with cyber security protections in order to demonstrate rigorous accounting of uncertainty through the architecture evaluation and selection. These case studies serve to define and demonstrate a new, more transparent and trusted architecture selection process that consistently provides better value for the stakeholders of a major system acquisition. While the examples in this research focused on U.S. DoD and other major acquisitions, the methodology developed is broadly applicable to other domains where this is a need for optimization of enterprise architectures as the basis for effective system acquisition. The results from the three case studies showed the new process outperformed the current methodology for conducting architecture evaluations in nearly all criteria considered and in particular selects architectures of better value, provides greater visibility into the actual decision making, and improves trust in the decision through a robust understanding of uncertainty. The primary contribution of this research then is improved information support to an architecture selection in the early phases of a system acquisition program. The proposed methodology presents a decision authority with an integrated assessment of each alternative, traceable to the concerns of the system's stakeholders, and thus enables a more informed and objective selection of the preferred alternative. It is recommended that the methodology proposed in this work is considered for future architecture evaluations

Cost optimization in requirements management for space systems

2021 Spring.Includes bibliographical references.When producing complex space systems, the transformation of customer needs into a realized system includes the development of product requirements. The ability to generate and manage the requirements can either enable the overall system development or drive significant cost and schedule impacts. Assessing practices in the industry and publications, it is observed that there is a substantial amount of documented approaches to address requirement development and product verification, but only a limited amount of documented approaches for requirements management. A complex system can have tens of thousands of requirements across multiple levels of development which, if not well managed, can lead to hidden costs associated with missed requirements and product rework. With current space system projects being developed at a rapid pace using more cost constrained approaches such as fixed budgets, an investigation into more efficient processes, such as requirements management, can yield methods to enable successful, cost effective system development. To address the optimal approach of managing requirements for complex space systems, this dissertation assesses current practices for requirements management, evaluates various contributing factors towards optimization of project costs associated with this activity, and proposes an optimized requirements management process to utilize during the development of space systems. Four key areas of process control are identified for requirements management optimization on a project, including utilization of a data focused requirements management approach, development (and review) of requirements using a collaborative software application, ensuring the requirement set is a consolidated with an appropriate amount of requirements for the project, and evaluating when to officially levy requirements on the product developers based on requirement maturation stability. Multiple case studies are presented to evaluate if the proposed requirements management process yields improvement over traditional approaches, including a simulation of the current state and proposed requirements management approaches. Ultimately, usage of the proposed optimized set of processes is demonstrated to be a cost effective approach when compared against traditional processes that may adversely impact the development of new space systems

WRT-1006 Technical Report: Developing the Digital Engineering Competency Framework (DECF) – Phase 2

17 USC 105 interim-entered record; under review.This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-19-D-003 (Task Order 0286).This material is based upon work supported, in whole or in part, by the U.S. Department of Defense through the Office of the Assistant Secretary of Defense for Research and Engineering (ASD(R&E)) under Contract HQ0034-19-D-003 (Task Order 0286). U.S. Government affiliation is unstated in article tex

Model-based Systems Engineering for Design, Management, and Governance of Protective Systems

The failure of protective systems can be catastrophic, and has its origin in management. Yet, most engineering works regarding protective systems focus on their physical components. Historically, protective systems have relied on a document-based approach, which implies handling several disjointed artifacts that are expensive to maintain and have a high potential for inconsistency and obsolescence. We present a framework that embeds management and governance in protective systems and harmonizes regulations, theories, and inconsistent industry guidelines. It pioneers the modeling of protective systems according to the tenors of model-based systems engineering (MBSE), which significantly reduces the pitfalls of its document-based counterpart. It provides a realistic approach to manage multiple aspects of change, and offers traceability, simulation, and visualization capabilities. First, we sketched a conceptual model that encompasses the physical components, management system, policy, laws and regulation, stakeholders and lifecycle, and stresses the importance of understanding the interactions among elements and their dynamic nature. Then, we used it as a baseline to develop the structure and behavior of our computerized model in SysML. Our MBSE framework advances the state of the art in safety-critical protective systems by integrating management and governance, and offering further capabilities inherent to the MBSE approach. It is suitable for combined design, operation, and regulation; it reduces the cost of maintenance of its artifacts; and it offers tools for simulation, impact analysis, and management of change. It supports shared governance and mitigates information asymmetry. Potential users include both enterprises and regulators from the chemical process safety industry and the energy sector, and any other agents invested in the design and management of protective systems. The model of protective systems developed in this research conforms to the standards issued by the Object Management Group (OMG) and the International Council on Systems Engineering (INCOSE). We believe that it may constitute a beginning point in the development of more sophisticated standards and both prescriptive and performance-based regulation for protective systems, intended to prevent catastrophic failures. It may also help regulators to synthesize and disseminate information, as they serve as an interface and mediator between companies and the general public

Expanded Guidance for NASA Systems Engineering. Volume 2: Crosscutting Topics, Special Topics, and Appendices

Historically, most successful NASA projects have depended on effectively blending project management, systems engineering, and technical expertise among NASA, contractors, and third parties. Underlying these successes are a variety of agreements (e.g., contract, memorandum of understanding, grant, cooperative agreement) between NASA organizations or between NASA and other Government agencies, Government organizations, companies, universities, research laboratories, and so on. To simplify the discussions, the term "contract" is used to encompass these agreements. This section focuses on the NASA systems engineering activities pertinent to awarding a contract, managing contract performance, and completing a contract. In particular, NASA systems engineering interfaces to the procurement process are covered, since the NASA engineering technical team plays a key role in the development and evaluation of contract documentation. Contractors and third parties perform activities that supplement (or substitute for) the NASA project technical team accomplishment of the NASA common systems engineering technical process activities and requirements outlined in this guide. Since contractors might be involved in any part of the systems engineering life cycle, the NASA project technical team needs to know how to prepare for, allocate or perform, and implement surveillance of technical activities that are allocated to contractors

A Building Information Modeling (BIM)-centric Digital Ecosystem for Smart Airport Life Cycle Management

An increasing number of new airport infrastructure construction and improvement projects are being delivered in today\u27s modern world. However, value creation is a recurring issue due to inefficiencies in managing capital expenditures (CapEx) and operating expenses (OpEx), while trying to optimize project constraints of scope, time, cost, quality, and resources. In this new era of smart infrastructure, digitalization transforms the way projects are planned and delivered. Building Information Modeling (BIM) is a key digital process technique that has become an imperative for today\u27s Architecture, Engineering, Construction and Operations (AECO) sector. This research suggests a BIM-centric digital ecosystem by detailing technical and strategic aspects of Airport BIM implementation and digital technology integration from a life cycle perspective. This research provides a novel approach for consistent and continuous use of digital information between business and functional levels of an airport by developing a digital platform solution that will enable seamless flow of information across functions. Accordingly, this study targets to achieve three objectives: 1- To provide a scalable know-how of BIM-enabled digital transformation; 2- To guide airport owners and major stakeholders towards converging information siloes for airport life cycle data management by an Airport BIM Framework; 3- To develop a BIM-based digital platform architecture towards realization of an airport digital twin for airport infrastructure life cycle management. Airport infrastructures can be considered as a System of Systems (SoS). As such, Model Based Systems Engineering (MBSE) with Systems Modeling Language (SysML) is selected as the key methodology towards designing a digital ecosystem. Applying MBSE principles leads to forming an integrating framework for managing the digital ecosystem. Furthermore, this research adopts convergent parallel mixed methods to collect and analyze multiple forms of data. Data collection tools include extensive literature and industry review; an online questionnaire; semi-structured interviews with airport owner parties; focus group discussions; first-hand observations; and document reviews. Data analysis stage includes multiple explanatory case study analyses, thematic analysis, project mapping, percent coverage analysis for coded themes to achieve Objective 1; thematic analysis, cluster analysis, framework analysis, and non-parametric statistical analysis for Objective 2; and qualitative content analysis, non-parametric statistical analysis to accomplish Objective 3. This research presents a novel roadmap toward facilitation of smart airports with alignment and integration of disruptive technologies with business and operational aspects of airports. Multiple comprehensive case study analyses on international large-hub airports and triangulation of organization-level and project-level results systematically generate scalable technical and strategic guidelines for BIM implementation. The proposed platform architecture will incentivize major stakeholders for value-creation, data sharing, and control throughout a project life cycle. Introducing scalability and minimizing complexity for end-users through a digital platform approach will lead to a more connected environment. Consequently, a digital ecosystem enables sophisticated interaction between people, places, and assets. Model-driven approach provides an effective strategy for enhanced decision-making that helps optimization of project resources and allows fast adaptation to emerging business and operational demands. Accordingly, airport sustainability measures -economic vitality, operational efficiency, natural resources, and social responsibility- will improve due to higher levels of efficiency in CapEx and OpEx. Changes in business models for large capital investments and introducing sustainability to supply chains are among the anticipated broader impacts of this study