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 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.

A Practical Guide to SysML: The Systems Modeling Language is a comprehensive guide to SysML for systems and software engineers. It provides an advanced and practical resource for modeling systems with SysML. The source describes the modeling language and offers information about employing SysML in transitioning an organization or project to model-based systems engineering. The book also presents various examples to help readers understand the OMG Systems Modeling Professional (OCSMP) Certification Program. The text is organized into four parts. The first part provides an overview of systems engineering. It explains the model-based approach by comparing it with the document-based approach and providing the modeling principles. The overview of SYsML is also discussed. The second part of the book covers a comprehensive description of the language. It discusses the main concepts of model organization, parametrics, blocks, use cases, interactions, requirements, allocations, and profiles. The third part presents examples that illustrate how SysML supports different model-based procedures. The last part discusses how to transition and deploy SysML into an organization or project. It explains the integration of SysML into a systems development environment. Furthermore, it describes the category of data that are exchanged between a SysML tool and other types of tools, and the types of exchange mechanisms that can be used. It also covers the criteria that must be considered when selecting a SysML. Software and systems engineers, programmers, IT practitioners, experts, and non-experts will find this book useful.*The authoritative guide for understanding and applying SysML*Authored by the foremost experts on the language*Language description, examples, and quick reference guide included

Worried about the growing complexity of systems in your organization? Manage it with recipes for applying agile methodologies and techniques in model-based systems engineering (MBSE) Key Features Learn how Agile and MBSE can work iteratively and collaborate to overcome system complexity Develop essential systems engineering products and achieve crucial enterprise objectives with easy-to-follow recipes Build efficient system engineering models using tried and trusted best practices Book DescriptionAgile MBSE can help organizations manage constant change and uncertainty while continuously ensuring system correctness and meeting customers’ needs. But deploying it isn’t easy. Agile Model-Based Systems Engineering Cookbook is a little different from other MBSE books out there. This book focuses on workflows – or recipes, as the author calls them – that will help MBSE practitioners and team leaders address practical situations that are part of deploying MBSE as part of an agile development process across the enterprise. Written by Dr. Bruce Powel Douglass, a world-renowned expert in MBSE, this book will take you through important systems engineering workflows and show you how they can be performed effectively with an agile and model-based approach. You’ll start with the key concepts of agile methods for systems engineering, but we won’t linger on the theory for too long. Each of the recipes will take you through initiating a project, defining stakeholder needs, defining and analyzing system requirements, designing system architecture, performing model-based engineering trade studies, all the way to handling systems specifications off to downstream engineering. By the end of this MBSE book, you’ll have learned how to implement critical systems engineering workflows and create verifiably correct systems engineering models.What you will learn Apply agile methods to develop systems engineering specifications Perform functional analysis with SysML Derive and model systems architectures from key requirements Model crucial engineering data to clarify systems requirements Communicate decisions with downstream subsystem implementation teams Verify specifications with model reviews and simulations Ensure the accuracy of systems models through model-based testing Who this book is for If you are a systems engineer who wants to pursue model-based systems engineering in an agile setting, this book will show you how you can do that without breaking a sweat. Fundamental knowledge of SysML is necessary; the book will teach you the rest.

This book is a contribution to the definition of a model based system engineering (MBSE) approach, designed to meet the objectives laid out by the INCOSE. After pointing out the complexity that jeopardizes a lot of system developments, the book examines fundamental aspects of systems under consideration. It goes on to address methodological issues and proposes a methodic approach of MBSE that provides, unlike current practices, systematic and integrated model-based engineering processes. An annex describes relevant features of the VHDL-AMS language supporting the methodological issues described in the book.

Systems Architecture Modeling with the Arcadia Method is an illustrative guide for the understanding and implementation of model-based systems and architecture engineering with the Arcadia method, using Capella, a new open-source solution. More than just another systems modeling tool, Capella is a comprehensive and extensible Eclipse application that has been successfully deployed in a wide variety of industrial contexts. Based on a graphical modeling workbench, it provides systems architects with rich methodological guidance using the Arcadia method and modeling language. Intuitive model editing and advanced viewing capabilities improve modeling quality and productivity, and help engineers focus on the design of the system and its architecture. This book is the first to help readers discover the richness of the Capella solution. - Describes the tooled implementation of the Arcadia method - Highlights the toolset widely deployed on operational projects in all Thales domains worldwide (defense, aerospace, transportation, etc.) - Emphasizes the author's pedagogical experience on the methods and the tools gained through conducting more than 80 training sessions for a thousand engineers at Thales University - Examines the emergence of an ecosystem of organizations, including industries that would drive the Capella roadmap according to operational needs, service and technology suppliers who would develop their business around the solution, and academics who would pave the future of the engineering ecosystem

Practical Model-Based Testing gives a practical introduction to model-based testing, showing how to write models for testing purposes and how to use model-based testing tools to generate test suites. It is aimed at testers and software developers who wish to use model-based testing, rather than at tool-developers or academics. The book focuses on the mainstream practice of functional black-box testing and covers different styles of models, especially transition-based models (UML state machines) and pre/post models (UML/OCL specifications and B notation). The steps of applying model-based testing are demonstrated on examples and case studies from a variety of software domains, including embedded software and information systems. From this book you will learn: - The basic principles and terminology of model-based testing - How model-based testing differs from other testing processes - How model-based testing fits into typical software lifecycles such as agile methods and the Unified Process - The benefits and limitations of model-based testing, its cost effectiveness and how it can reduce time-to-market - A step-by-step process for applying model-based testing - How to write good models for model-based testing - How to use a variety of test selection criteria to control the tests that are generated from your models - How model-based testing can connect to existing automated test execution platforms such as Mercury Test Director, Java JUnit, and proprietary test execution environments - Presents the basic principles and terminology of model-based testing - Shows how model-based testing fits into the software lifecycle, its cost-effectiveness, and how it can reduce time to market - Offers guidance on how to use different kinds of modeling techniques, useful test generation strategies, how to apply model-based testing techniques to real applications using case studies

The practice of Model-Based Systems Engineering (MBSE) is becoming more widely adopted in industry, academia and commerce; as the use of modelling matures in the real world, so the need increases for more guidance on how to model effectively and efficiently. This practical book describes a number of systems-level "patterns" that may be applied using the systems modelling language SysML for the development of any number of different applications and as the foundations for a system model. This is a companion volume to both SysML for Systems Engineering: A Model-Based Approach and Model-based Requirements Engineering, both published by the IET. Whereas the previous volumes presented the case for modelling and provided an indepth overview of SysML, this book focuses on a set of "patterns" as the basis of an MBSE model and their use in today's systems engineering community. Topics covered include an introduction to MBSE concepts, ontology and frameworks; what is a pattern?; interface definition pattern; traceability pattern; test case pattern; epoch/measurement pattern; life cycle pattern; evidence pattern; description pattern; context pattern; analysis risk pattern; requirements engineering - ACRE; system of systems requirements - SoS-ACRE; process modelling - '7 views'; competency modelling; life cycle management; project information modelling; model maturity levels; technology readiness levels; defi ning the patterns; using patterns for model assessment, model definition, and model retro-fitting. Foundations for Model-Based Systems Engineering is essential reading for researchers and students of systems modelling in academia, as well as systems engineers, requirements engineers, software engineers, systems managers, requirements managers, and systems modelers in industry.

This primer addresses the basic concepts of model-based systems engineering. It covers the Model, Language, Behavior, Process, Architecture, and Verification and Validation. It is a call to consider the foundational principles behind those concepts. It is not designed to present novel insights into MBSE so much as to provide a guided tour of the touchstones of systems design. It is a guide to the new MBSE acolyte and a reminder to the experienced practitioner. It is our hope that you find this primer valuable. We welcome your comments and suggestions about improving it. Much of what we have learned about how it should be organized and presented has come from thoughtful contributions from the readers of the 1st edition.

For the last century, the automotive industry has been dominated by internal combustion engines. Their flexibility of application, driving range, performance and sporty characteristics has resulted in several generations of this technology and has formed generations of engineers. But that is not the end of the story. Stricter legislation and increased environmental awareness have resulted in the development of new powertrain technologies in addition and parallel to the highly optimized internal combustion engine. Hybrid powertrains systems, pure battery electric systems and fuel cell systems, in conjunction with a diverse range of applications, have increased the spectrum of powertrain technologies. Furthermore, automated driving together with intelligent and highly connected systems are changing the way to get from A to B. Not only is the interaction of all these new technologies challenging, but also several different disciplines have to collaborate intensively in order for new powertrain systems to be successfully developed. These new technologies and the resulting challenges lead to an increase in system complexity. Approaches such as systems engineering are necessary to manage this complexity. To show how systems engineering manages the increasing complexity of modern powertrain systems, by providing processes, methods, organizational aspects and tools, this book has been structured into five parts. Starting with Challenges for Powertrain Development, which describes automotive-related challenges at different levels of the system hierarchy and from different point of views. The book then continues with the core part, Systems Engineering, in which all the basics of systems engineering, model-based systems engineering, and their related processes, methods, tools, and organizational matters are described. A special focus is placed on important standards and the human factor. The third part, Automotive Powertrain Systems Engineering Approach, puts the fundamentals of systems engineering into practice by adding the automotive context. This part focuses on system development and also considers the interactions to hardware and software development. Several approaches and methods are presented based on systems engineering philosophy. Part four, Powertrain Development Case Studies, adds the practical point of view by providing a range of case studies on powertrain system level and on powertrain element level and discusses the development of hybrid powertrain, internal combustion engines, e-drives, transmissions, batteries and fuel cell systems. Two case studies on a vehicle level are also presented. The final part, Outlook, considers the development of systems engineering itself with particular focus on information communication technologies. Even though this book covers systems engineering from an automotive perspective, many of the challenges, fundamental principles, conclusions and outlooks can be applied to other domains too. Therefore, this book is not only relevant for automotive engineers and students, but also for specialists in scientific and industrial positions in other domains and anyone who has to cope with the challenge of successfully developing complex systems with a large number of collaborating disciplines.