Systems Engineering In Context

This volume chronicles the 16th Annual Conference on System Engineering Research (CSER) held on May 8-9, 2018 at the University of Virginia, Charlottesville, Virginia, USA. The CSER offers researchers in academia, industry, and government a common forum to present, discuss, and influence systems engineering research. It provides access to forward‐looking research from across the globe, by renowned academicians as well as perspectives from senior industry and government representatives. Co‐founded by the University of Southern California and Stevens Institute of Technology in 2003, CSER has become the preeminent event for researchers in systems engineering across the globe. Topics include though are not limited to the following: Systems in context: · Formative methods: requirements · Integration, deployment, assurance · Human Factors · Safety and Security Decisions/ Control & Design; Systems Modeling: · Optimization, Multiple Objectives, Synthesis · Risk and resiliency · Collaborative autonomy · Coordination and distributed decision-making Prediction: · Prescriptive modeling; state estimation · Stochastic approximation, stochastic optimization and control Integrative Data engineering: · Sensor Management · Design of Experiments

This book focuses on systems engineering, systems thinking, and how that thinking can be learned in practice. It describes a novel analytical framework based on activity theory for understanding how systems thinking evolves and how it can be improved to support multidisciplinary teamwork in the context of system development and systems engineering. This method, developed using data collected over four years from three different small space systems engineering organizations, can be applied in a wide variety of work activities in the context of engineering design and beyond in order to monitor and analyze multidisciplinary interactions in working teams over time. In addition, the book presents a practical strategy called WAVES (Work Activity for a Evolution of Systems engineering and thinking), which fosters the practical learning of systems thinking with the aim of improving process development in different industries. The book offers an excellent resource for researchers and practitioners interested in systems thinking and in solutions to support its evolution. Beyond its contribution to a better understanding of systems engineering, systems thinking and how it can be learned in real-world contexts, it also introduce a suitable analysis framework that helps to bridge the gap between the latest social science research and engineering research.

This book discusses the concepts, tools and applications of systems engineering. Chapter One presents the implementation of automated measuring system for measuring chromatic dispersion (CD). Chapter Two discusses the results regarding the optimization of phase based EOM (electro optical modulator) as the most important component in CD measurement setup, then investigates the results of CD measurement characterizations based on different lengths of fiber, different wavelengths and different RF frequencies. Chapter Three provides a review on optical waveguide sensor using ion-exchange technology. Chapter Four examines silver nano particle ion-exchanged glass waveguide technology. Chapter Five highlights the major advantages of using graphical modelling languages in a Model-Based Systems Engineering (MBSE) context and describes the main features of SysML, the modeling language that the authors believe to be "the dialect" for MBSE. Chapter Six provides a complex system analysis for engineering of systemic failures.

Systems engineering is a mandatory approach in some industries, and is gaining wider acceptance for complex projects in general. However, under the imperative of delivering these projects on time and within budget, the focus has been mainly on the management aspects, with less attention to improving the core engineering activity – design. This book addresses the application of the system concept to design in several ways: by developing a deeper understanding of the system concept, by defining design and its characteristics within the process of engineering, and by applying the system concept to the early stage of design, where it has the greatest impact. A central theme of the book is that the purpose of engineering is to be useful in meeting the needs of society, and that therefore the ultimate measure of the benefit of applying the system concept should be the extent to which it advances the achievement of that purpose. Consequently, any consistent, top-down development of the functionality required of a solution to the problem of meeting a defined need must proceed from such a measure, and it is agued that a generalised form of Return on Investment is an appropriate measure. A theoretical framework for the development of functionality based on this measure and utilising the system concept is presented, together with some examples and practical guidelines.

This book provides a broad overview of the benefits from a Systems Engineering design philosophy in architecting complex systems composed of artificial intelligence (AI), machine learning (ML) and humans situated in chaotic environments. The major topics include emergence, verification and validation of systems using AI/ML and human systems integration to develop robust and effective human-machine teams—where the machines may have varying degrees of autonomy due to the sophistication of their embedded AI/ML. The chapters not only describe what has been learned, but also raise questions that must be answered to further advance the general Science of Autonomy. The science of how humans and machines operate as a team requires insights from, among others, disciplines such as the social sciences, national and international jurisprudence, ethics and policy, and sociology and psychology. The social sciences inform how context is constructed, how trust is affected when humans and machines depend upon each other and how human-machine teams need a shared language of explanation. National and international jurisprudence determine legal responsibilities of non-trivial human-machine failures, ethical standards shape global policy, and sociology provides a basis for understanding team norms across cultures. Insights from psychology may help us to understand the negative impact on humans if AI/ML based machines begin to outperform their human teammates and consequently diminish their value or importance. This book invites professionals and the curious alike to witness a new frontier open as the Science of Autonomy emerges.

This book will change the way you think about problems. It focuses on creating solutions to all sorts of complex problems by taking a practical, problem-solving approach. It discusses not only what needs to be done, but it also provides guidance and examples of how to do it. The book applies systems thinking to systems engineering and introduces several innovative concepts such as direct and indirect stakeholders and the Nine-System Model, which provides the context for the activities performed in the project, along with a framework for successful stakeholder management. A list of the figures and tables in this book is available at https://www.crcpress.com/9781138387935. FEATURES • Treats systems engineering as a problem-solving methodology • Describes what tools systems engineers use and how they use them in each state of the system lifecycle • Discusses the perennial problem of poor requirements, defines the grammar and structure of a requirement, and provides a template for a good imperative construction statement and the requirements for writing requirements • Provides examples of bad and questionable requirements and explains the reasons why they are bad and questionable • Introduces new concepts such as direct and indirect stakeholders and the Shmemp! • Includes the Nine-System Model and other unique tools for systems engineering