Model Oriented Systems Engineering Science

Systems engineering (SE) is experiencing a significant expansion that encompasses increasingly complex systems. However, a common body of knowledge on how to apply complex systems engineering (CSE) has yet to be developed. A combination of people and other autonomous agents, crossing organization boundaries and continually changing, these hybrid systems are less predictable while being more self-organizing and adaptive than traditional systems. The growing pains of this evolution and the ever-widening reach of SE technology require an effective foundation for integrating traditional and complex engineering methods, addressing machine and human interaction, as well as scaling up and down, from nano scale to the macro system-of-systems level. Model-oriented Systems Engineering Science: A Unifying Framework for Traditional and Complex Systems addresses solutions to that expansion and integration problem. This text takes advantage of better-understood systems science (SS) to support the transition, identifying and using commonalities between complex systems and other sciences, such as biology, sociology, cognitive science, organizational theory, and computational science. The author defines Model-oriented Systems Engineering Science (MOSES), an organized system that selects appropriate information from these disciplines and unifies it into a coherent framework. The result is a seamless approach to the class of systems across the extended scope of the new SE—a foundation upon which to develop an enhanced and unified SE. Modeling orientation (MO) provides a common perspective on the entire SES/SE enterprise, including all supporting sciences, engineering for the full range of traditional, complex, and hybrid systems, and their management. This book extends existing modeling approaches into an MO that views all science artifacts and engineering artifacts as models of systems. It organizes them into a virtual structured repository called the "SE model space"—effectively a container for the accumulating body of SE and SES knowledge in the form of models and patterns. By organizing and integrating all these elements into a common framework, the author makes the material not only easily accessible but also immediately applicable, and provides a well-grounded basis for future growth and evolution of the SE discipline.

This textbook presents a proven, mature Model-Based Systems Engineering (MBSE) methodology that has delivered success in a wide range of system and enterprise programs. The authors introduce MBSE as the state of the practice in the vital Systems Engineering discipline that manages complexity and integrates technologies and design approaches to achieve effective, affordable, and balanced system solutions to the needs of a customer organization and its personnel. The book begins with a summary of the background and nature of MBSE. It summarizes the theory behind Object-Oriented Design applied to complex system architectures. It then walks through the phases of the MBSE methodology, using system examples to illustrate key points. Subsequent chapters broaden the application of MBSE in Service-Oriented Architectures (SOA), real-time systems, cybersecurity, networked enterprises, system simulations, and prototyping. The vital subject of system and architecture governance completes the discussion. The book features exercises at the end of each chapter intended to help readers/students focus on key points, as well as extensive appendices that furnish additional detail in particular areas. The self-contained text is ideal for students in a range of courses in systems architecture and MBSE as well as for practitioners seeking a highly practical presentation of MBSE principles and techniques.

Model-Based Systems Engineering (MBSE), which tackles architecting and design of complex systems through the use of formal models, is emerging as the most critical component of systems engineering. This textbook specifies the two leading conceptual modeling languages, OPM—the new ISO 19450, composed primarily by the author of this book, and OMG SysML. It provides essential insights into a domain-independent, discipline-crossing methodology of developing or researching complex systems of any conceivable kind and size. Combining theory with a host of industrial, biological, and daily life examples, the book explains principles and provides guidelines for architecting complex, multidisciplinary systems, making it an indispensable resource for systems architects and designers, engineers of any discipline, executives at all levels, project managers, IT professional, systems scientists, and engineering students.

Model-Based Systems Engineering explains the fundamental theories behind model-based systems and the considerations involved in applying theory to the design of real systems. The book begins by presenting terms used in systems engineering and introducing the discrete system and its components. The remainder of the text explains topics such as the mathematical theory of system coupling, the homomorphic relationship between systems, the concept of system mode, the mathematical structure of T3SD system requirements, and the implications of that structure for T3SD system design. Appendices include a short bibliography, detailed definitions of all examples discussed in the text, a list of all notations used, and an index. Model-Based Systems Engineering is an excellent text for engineering students, and an invaluable reference for engineers and scientists.

This handbook brings together diverse domains and technical competences of Model Based Systems Engineering (MBSE) into a single, comprehensive publication. It is intended for researchers, practitioners, and students/educators who require a wide-ranging and authoritative reference on MBSE with a multidisciplinary, global perspective. It is also meant for those who want to develop a sound understanding of the practice of systems engineering and MBSE, and/or who wish to teach both introductory and advanced graduate courses in systems engineering. It is specifically focused on individuals who want to understand what MBSE is, the deficiencies in current practice that MBSE overcomes, where and how it has been successfully applied, its benefits and payoffs, and how it is being deployed in different industries and across multiple applications. MBSE engineering practitioners and educators with expertise in different domains have contributed chapters that address various uses of MBSE and related technologies such as simulation and digital twin in the systems lifecycle. The introductory chapter reviews the current state of practice, discusses the genesis of MBSE and makes the business case. Subsequent chapters present the role of ontologies and meta-models in capturing system interdependencies, reasoning about system behavior with design and operational constraints; the use of formal modeling in system (model) verification and validation; ontology-enabled integration of systems and system-of-systems; digital twin-enabled model-based testing; system model design synthesis; model-based tradespace exploration; design for reuse; human-system integration; and role of simulation and Internet-of-Things (IoT) within MBSE.

This comprehensive resource provides systems engineers and practitioners with the analytic, design and modeling tools of the Model-Based Systems Engineering (MBSE) methodology of Integrated Systems Engineering (ISE) and Pipelines of Processes in Object Oriented Architectures (PPOOA) methodology. This methodology integrates model based systems and software engineering approaches for the development of complex products, including aerospace, robotics and energy domains applications. Readers learn how to synthesize physical architectures using design heuristics and trade-off analysis. The book provides information about how to identify, classify and specify the system requirements of a new product or service. Using Systems Modeling Language (SysML) constructs, readers will be able to apply ISE & PPOOA methodology in the engineering activities of their own systems.

This volume comprises papers from the 18th Conference on Systems Engineering Research (CSER). The theme of this volume, “Recent Trends and Advances in Model-Based Systems Engineering,” reflects the fact that systems engineering is undergoing a transformation motivated by mission and system complexity and enabled by technological advances such as model-based systems engineering, digital engineering, and the convergence of systems engineering with other disciplines. This conference is focused on exploring recent trends and advances in model-based systems engineering (MBSE) and the synergy of MBSE with simulation technology and digital engineering. Contributors have submitted papers on MBSE methods, modeling approaches, integration of digital engineering with MBSE, standards, modeling languages, ontologies and metamodels, and economics analysis of MBSE to respond to the challenges posed by 21st century systems. What distinguishes this volume are the latest advances in MBSE research, the convergence of MBSE with digital engineering, and recent advances in applied research in MBSE, including growing convergence with systems science and decision science. This volume is appropriate as a reference text in graduate engineering courses in Model-Based Systems Engineering.

Get to grips with systems engineering life cycles, processes, and best practices and discover techniques to successfully develop complex systems Key Features Discover how to manage increased complexity and understand systems better via effective communication Adopt a proven model-based approach for systems engineering in your organization Apply proven techniques for requirements, design, validation and verification, and systems engineering management Book DescriptionSystems engineering helps us to understand, specify, and develop complex systems, and is applied across a wide set of disciplines. As systems and their associated problems become increasingly complex in this evermore connected world, the need for more rigorous, demonstrable, and repeatable techniques also increases. Written by Professor Jon Holt – an internationally recognized systems engineering expert – this book provides a blend of technical and business aspects you need to understand in order to develop successful systems. You'll start with systems engineering basics and understand the complexity, communication, and different stakeholders' views of the system. The book then covers essential aspects of model-based systems engineering, systems, life cycles, and processes, along with techniques to develop systems. Moving on, you'll explore system models and visualization techniques, focusing on the SysML, and discover how solutions can be defined by developing effective system design, verification, and validation techniques. The book concludes by taking you through key management processes and systems engineering best practices and guidelines. By the end of this systems engineering book, you'll be able to confidently apply modern model-based systems engineering techniques to your own systems and projects.What you will learn Understand the three evils of systems engineering - complexity, ambiguous communication, and lack of understanding Realize successful systems using model-based systems engineering Understand the concept of life cycles and how they control the evolution of a system Explore processes and related concepts such as activities, stakeholders, and resources Discover how needs fit into the systems life cycle and which processes are relevant and how to comply with them Find out how design, verification, and validation fit into the life cycle and processes Who this book is for This book is for aspiring systems engineers, engineering managers, or anyone looking to apply systems engineering practices to their systems and projects. While a well-structured, model-based approach to systems engineering is an essential skill for engineers of all disciplines, many companies are finding that new graduates have little understanding of systems engineering. This book helps you acquire this skill with the help of a simple and practical approach to developing successful systems. No prior knowledge of systems engineering or modeling is required to get started with this book.