Model Based Systems Engineering (MBSE) is now widely accepted throughout the industry, from commercial to aerospace and defense. However, while we understand and accept the principles of MBSE, successful adoption and implementation is still a challenge within the industry. The migration from document‐based systems engineering processes to MBSE requires more than purchasing tools and a one‐week course on Systems Modeling Language (SysML). MBSE does not change the practice of Systems Engineering as defined in the INCOSE SE Handbook or ISO/IEEE 15288, but it does affect the way in which systems engineering processes are implemented and supported within and across organizations. Organizations adopting MBSE must address issues such as new skill and competency requirements for systems engineers, model and data management over the lifecycle of the system, and integration with other engineering tools and processes, among others. It is not a tool problem or a modeler problem. It is an enterprise problem and requires an enterprise approach. The approach must be defined and guided by an enterprise architecture, which is broader than just the engineering tools and their interfaces. It includes the enterprise strategic vision, capabilities, operational concepts, organizations, and material solutions required to achieve MBSE adoption, how they relate to one another, and their evolution over time. This paper provides a broad overview of the fundamentals of MBSE adoption and the broader effort of digital engineering transformation, presenting the digital engineering environment as a system‐of‐systems. It presents the use of enterprise architecture as a roadmap for MBSE adoption within the industry.
Abstract. Throughout the Systems Engineering Lifecycle events require personnel, systems, equipment, facilities and information to converge on time and at the right place in order to achieve a program objective. Unpredictability in any predecessor event can mean unpredictability for the overall project. The Last Planner is a production and planning method initially deployed in 1992 in the building construction industry as part of an effort to reduce work flow variability and improve production efficiency in the construction industry. The two key elements of the Last Planner are (1) a change in project management from a task-oriented to a work-flow oriented model and (2) processes to improve reliability of the workflow within the team or group performing the work. This paper examines the systems engineering lifecycle as a production lifecycle and explores the application of key elements of the Last Planner as a tool for system engineers to address uncertainty and unpredictability in the execution of a project.
In their paper on “A Generalized Systems Engineering Reuse Framework and Its Cost Estimating Relationships,” (Wang, Roedler, et al. 2014) present an approach for estimation of systems engineering effort that extends the COSYSMO equation to account for the effort associated with Design With Reuse and Design For Reuse classification categories in the Generalized Reuse Framework. Implementation of this approach for cost estimation clearly depends on two critical items: (1) the ability to accurately and consistently count the size drivers; and (2) the ability to calibrate the model equation. As part of future work, they also describe the potential to use this approach as a management tool in architecture development – “a cataloging mechanism in organizing components of reference architecture.” This paper presents a practical implementation of the COSYSMO cost estimating relationship through extension of a Model Based Systems Engineering (MBSE) modeling environment with SysML for estimating end‐to‐end systems engineering effort in developing a system. The approach provides a new way of rapidly creating cost estimates, conducting cost‐based analysis and trade studies with full traceability from the cost estimation parameters back to the architecture of referenced system of interest.
Over the past several years, numerous industries have increased their adoption of the systems modeling language (SysML®) and model-based systems engineering (MBSE) as a core practice within their engineering lifecycles. However, the introduction of SysML and MBSE methodologies has not yet yielded many of the originally envisioned benefits. System models are becoming larger and more complex and many large MBSE projects continue to experience problems with model integration, repository performance, and model lifecycle management. The root cause is the failure to recognize the MBSE digital environment as a complex engineering information processing system that requires the same rigor and development processes as the system-ofinterest (SoI) it is designing. This article describes how three future of systems engineering (FuSE) agility foundation concepts (system of innovation, effective stakeholder engagement, and continuous integration) directly address some of the problems seen in adoption, deployment, and sustainment of the MBSE digital environment as an SoI.
The rapid adoption and advancement of Model Based Systems Engineering (MBSE) methods and tools opens up new avenues of systems engineering practices. One of them is cost estimation. As a key enabler for affordability analysis and budgetary decision making, cost estimation is an essential component for all system development and sustainment efforts. However, cost estimation is typically a separate endeavor from the design and development effort, creating a professional “chasm” between the worlds of systems designers and of cost analysts, causing a disconnect between the system as designed and the cost and effort required to build it. This paper describes an approach to “tightly” integrate the existing practice of parametric cost estimation with the system architecture development process by leveraging MBSE and SysML to enable repeatable and efficient estimation of system development cost, and to allow system cost and affordability to be incorporated into the “digital thread” of the design while improving the efficiency and effectiveness of the cost estimation process. By expanding our previous work (Papke, Wang and Pavalkis 2017), this paper describes a new concept of operation (CONOP) for system development, enabled by the integrated SysML and COSYSMO modeling environment, that effectively connects the cost baselines to the technical baselines throughout the project life cycle. This new CONOP presents another step towards “pulling the digital thread” by making affordability and economic analysis an integral part of the system architecture.
The agile, evolving threat environment and the increasing cost of damage being inflicted is placing tremendous pressure on the systems engineering discipline to design and implement effective security capabilities. One promising approach is the application of agile systems architecture to the design of system security. In order to be successful, however, systems engineers and security engineers will need to adopt a common design language and a common reference architecture that supports the definition and design of a system that has both resilience and continuous evolution of security capability. This paper presents an approach to overcome these obstacles through application of model‐based systems engineering and use of enterprise architecture frameworks to address specific elements of an agile systems architecture which resides in both the design time and operating time domains.
The SOFIA data system must meet numerous technical and organizational objectives, including widely available distribution to support integration and testing at users' institutions. As with all professional data system software development, a wide range of sophisticated development tools are required. With open source software now widely available, it is possible to build an advanced Unix-based development environment taking full advantage of freely available tools. This paper analyzes advantages and disadvantages of this approach, the selection processes used, and the list of tools selected to date for the SOFIA development effort.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.