Model-Based Systems Engineering With OPM And SysML
LINK ---> https://urlgoal.com/2tkXQn
Provides a holistic, formal, yet intuitive approach to developing and evolving complex systems, embedded systems, and systems of systems that can comprise humans, hardware, software, and regulations, which can be physical and cybernetic components, operating in harmony with the environment
Professor Dov Dori is Harry Lebensfeld Chair in Industrial Engineering and Head of the Enterprise System Modeling Laboratory at the Faculty of Industrial Engineering and Management, Technion, Israel Institute of Technology. Since 2000 he has been intermittently Visiting Professor at MIT's Engineering Systems Division, where he is currently Lecturer. He received his PhD in Computer Science in 1988 from Weizmann Institute of Science, MSc in Operations Research from Tel Aviv University in 1981, and BSc in Industrial Engineering and Management from Technion in 1975. His research interests include model-based systems engineering, conceptual modeling of complex systems, systems architecture and design, software and systems engineering, and systems biology.
In June 2008, Richard Martin approached Dov Dori after his presentation at the INCOSE International Symposium in Utrecht, the Netherlands, to inquire about the possibility of creating an International Standard for OPM. Martin, convener of ISO TC184/SC5/WG1 for automation systems interoperability architecture and modelling, had for some time been searching for methodologies offering more than static information and process modeling. He provided Dori with a simple example to model that could demonstrate both the modelling capability of OPM and its dynamic simulation opportunity.
The OPM Study Group began its work in October 2010 and issued an interim report for the 2011 SC5 Plenary. The report included several uses of OPM to model existing SC5 standards and led to an initial motivation for the standardization of OPM with the realization that being text-based, ISO standards are prone to suffer from inconsistencies and incomplete information. This deficiency could be significantly reduced if the standards were model-based rather than text-based, and OPM offered a useful underlying modeling paradigm for this purpose.
A final OPM Study Group Report and a draft for a metamodel for model-based standards authoring document were delivered at the 2012 SC5 Plenary. As the OPM Study Group effort progressed, it became obvious that OPM could also serve as a solid and comprehensive basis for model-based systems engineering (MBSE) and for modeling both natural and man-made systems.
While both languages aim at the same purpose of providing a means for general-purpose systems engineering, these languages take different approaches in realizing this goal. SysML is a profile of UML (Unified Modeling Language).
No Magic cuts through the complexity of sharing information among engineering teams from the start. As a result, the end product we want to build is likely to be better designed, with better outcomes and fewer surprises at later stages of the project. That saves time and money.
V&V helps minimize late defect discovery by engineering and manufacturing functions orchestrated by systems engineering costs more with issue discovery near the end. It is good to know about serious issues sooner, rather than later.
In 2007, a formal survey of candidate MBSE methodologies was published as part of the work of the INCOSE MBSE Focus Group that later was formalized as the INCOSE MBSE Initiative. In 2008, that formal survey of candidate MBSE methodologies was published under the auspices of an INCOSE technical publication [see Estefan, 2008 under INCOSE Links below]. The 2008 report surveyed six (6) candidate MBSE methodologies: INCOSE Object-Oriented Systems Engineering Method (OOSEM), IBM Rational Telelogic Harmony-SE, IBM Rational Unified Process for Systems Engineering (RUP-SE), Vitech MBSE Methodology, JPL State Analysis (SA), and Dori Object-Process Methodology (OPM). It should be noted that the scope of the report went beyond a simple survey and also documented a number of key issues related to the discipline of MBSE, including the following: differentiating processes, methods, and tools; characterizing the role of lifecycle models (project, acquisition, and systems engineering); an explanation of models in support of MBSE processes; and, documenting the roles of model-based hazard analysis, UML/OMG SysML, OMG model-driven architecture (MDA), and executable UML foundation.
A systems and scenario analytic approach will be used to think through and integrate the diversepolitical, economic, societal, and technological factors that shape the future. The construction ofalternative scenarios enables multiple stakeholders with different points of view to think throughthe consequences of action and interactions. The point of the analysis is not to predict the future,but rather to identify opportunities and risks that individuals and organizations may face so thatthey are better prepared to seize opportunities and to manage risks effectively. Strategicleadership requires an understanding of the trends that influence increasingly interconnected andinterdependent systems of systems and that directly influence the quality of our lives. Thecourse is an introduction to a holistic way of understanding the current state, and possible futurestates of the world and the human condition given differences in cultures, values, and beliefs.
Students work on projects to address large, complex and seeminglyintractable real-world problems, such as energy supply,environmental issues, health care delivery, and critical infrastructure(e.g., telecommunications, water supply, and transportation).Introduces interdisciplinary approaches - rooted in engineering,management, and the social sciences - for considering these criticalcontemporary issues. Small, faculty-led teams select an engineeringsystems term project to illustrate several of these approaches.
The assignments will step through the processes of problem definition, scoping, formulation, modelcreation, validation, analysis, and results presentation. The students will work in small teams forconducting in-depth analysis of system behavior, performance, and simulated outcomes.The overall goal of the course is to enable students to: (1) Understand key properties of complex adaptivesystems that can limit impact of interventions and policies; (2) Gain familiarity with methods and tools forstudying system behavior and understand their strengths and limitations; and (3) Systematicallyconceptualize and build simulation models for conducting quantitative analysis.
Introduction to systems thinking and the processes and methods of systems engineering. The course covers fundamentals of systems engineering and system architecting, requirements analysis, functional analysis and allocation, preliminary system architecture, systems analysis, system design, and the basics of test and evaluation. Various perspectives, from frameworks, processes, and standards, such as the DoD Architecture Framework (DoDAF), DoD Joint Capabilities Integration and Development System (JCIDS), EIA 632, ISO 15288, IEEE 1220, IEEE 1471, and the International Council on Systems Engineering (INCOSE) models, are presented. Students analyze case studies. Students also use spreadsheet software for modeling and analyzing requirements and conceptual design alternatives. The course includes the application of fundamental systems engineering processes and methods to an integrative project, as well as development of communication skills through oral presentations and written reports.
Complex Systems lie at the heart of a variety of large-scale phenomena of great significance - global warming, ice ages, water, poverty, pandemics - and this text uses these case studies as motivations and contexts to explore complex systems and related topics of nonlinear dynamics and power-law statistics. Although detailed mathematical descriptions of these topics can be challenging, the consequences of a system being nonlinear, power-law, or complex are in fact quite accessible. This book blends a tutorial approach to the mathematical aspects of complex systems together with a complementary narrative on the global/ecological/societal implications of such systems.
Nearly all engineering undergraduate courses focus on mathematics and systems which are small scale, linear, and Gaussian. Unfortunately there is not a single large-scale ecological or social phenomenon that is scalar, linear, and Gaussian. This book offers insights to better understand the large-scale problems facing the world and to realize that these cannot be solved by a single, narrow academic field or perspective. Instead, the book seeks to emphasize understanding, concepts, and ideas, in a way that is mathematically rigorous, so that the concepts do not feel vague, but not so technical that the mathematics get in the way. The book is intended for students in technical domains such as engineering, computer science, physics, mathematics, and environmental studies.
Systems Engineering: Principles and Practice, 3rd Edition is the leading interdisciplinary reference for systems engineers. The up-to-date third edition provides readers with discussions of model-based systems engineering, requirements analysis, engineering design, and software design. Freshly updated governmental and commercial standards, architectures, and processes are covered in-depth. The book includes newly updated topics on:
Examples and exercises appear throughout the text, allowing the reader to gauge their level of retention and learning. Systems Engineering: Principles and Practice was and remains the standard textbook used worldwide for the study of traditional systems engineering. The material is organized in a manner that allows for quick absorption of industry best practices and methods.
The mathematization of the sciences, of engineering, and of economics has been an outstandingly successful intellectual enterprise, enabling the modern world. As the operations of the world become more and more dependent on highly interconnected, massively complex, networked systems of computational devices, the need to develop a mathematical understanding of their properties and behaviours is increasingly pressing. 59ce067264