Modeling and Managing Interdependent Complex Systems of Systems

Nine innovative methods to think outside the box and solve complex system problems Managing Complex Systems provides specific tools and guidance needed to be a more creative and innovative thinker. Following the author's methodology, the reader will be better able to devise and implement nontraditional solutions to seemingly intractable complex problems. By challenging the reader to think in new and creative ways, the book offers a road map to success, whether measured in terms of competitive advantage, greater market share, improved productivity, or higher profits, all based upon better solutions to difficult problems. The first four chapters set the foundation for creative thinking by exploring the nature of large-scale systems and complexity, thinking inside and outside the box, and examples of how an inventive mind solves problems in both management and scientific domains. Subsequent chapters address nine focused methods that the author has formulated to help the reader think outside the box: * Broaden and generalize * Crossover * Question conventional wisdom * Back of the envelope * Expanding the dimensions * Obversity * Remove constraints * Thinking with pictures * Systems approach Real-life examples are provided for each method that demonstrate how the approach enhances problem solving and decision making in system development and management. Following the discussion of the nine methods, the author examines group decision making as well as additional creative thinking procedures devised by other researchers, including references that assist in exploring these methods in greater detail. The author ends with a wrap-up chapter that includes a test to help readers practice their tendencies toward creative thinking skills and action with respect to solving real-world problems. The nine methods discussed in this book have broad applicability and can be used successfully by managers with a wide range of responsibilities in business and technology. For anyone who is tired of the same old approach with the same old results, this book is essential reading.

Explains multi-level models of enterprise systems and covers modeling methodology This book addresses the essential phenomena underlying the overall behaviors of complex systems and enterprises. Understanding these phenomena can enable improving these systems. These phenomena range from physical, behavioral, and organizational, to economic and social, all of which involve significant human components. Specific phenomena of interest and how they are represented depend on the questions of interest and the relevant domains or contexts. Modeling and Visualization of Complex Systems and Enterprises examines visualization of phenomena and how understanding the relationships among phenomena can provide the basis for understanding where deeper exploration is warranted. The author also reviews mathematical and computational models, defined very broadly across disciplines, which can enable deeper understanding. Presents a 10 step methodology for addressing questions associated with the design or operation of complex systems and enterprises Examines six archetypal enterprise problems including two from healthcare, two from urban systems, and one each from financial systems and defense systems Provides an introduction to the nature of complex systems, historical perspectives on complexity and complex adaptive systems, and the evolution of systems practice Modeling and Visualization of Complex Systems and Enterprises is written for graduate students studying systems science and engineering and professionals involved in systems science and engineering, those involved in complex systems such as healthcare delivery, urban systems, sustainable energy, financial systems, and national security.

In the field of aeronautical dynamics, this book offers readers a design tool which enables them to solve the different problems that can occur during the planning stage of a private project. The authors present a system for the modeling, design and calculation of the flying qualities of airplanes and drones, with a complete mathematical model by Matlab/Simulink. As such, this book may be useful for design engineers as well as for keen airplane amateurs. The authors expound the various phases involved in the design process of an airplane, starting with the formulation of a design tool, under the form of a 0D mathematical model (dimensionless, time dependent), before moving on to explore the behavior of the airplane under certain circumstances and offering insights into the optimization of airplane flying qualities. As validation of this model, they present a numerical result, drawn from data collected on an existing plane – the Concorde. The dimensional process is then explored and applied to a realistic drone project. Recommendations on the development of the principal characteristics of the plane (i.e. mass distribution, air load, wing span) are given. Contents 1. 0D Analytical Modeling of theAirplane Motions. 2. Design and Optimizationof an Unmanned Aerial Vehicle (UAV). 3. Organization of the Auto-Pilot. This book provides a description of the modeling, design, and calculation of the aeronautical qualities of airplanes and drones. Divided into several parts, this book first summarizes all the necessary theoretical developments about the equations of motions and trajectory calculations of the machine. It then goes on to describe practical building processes and considers piloting methods. The last part makes a comparison between theoretical calculations and measured recorded data of the real flying machine. Accompanied by a complete mathematical model in MATLAB/SIMULINK

Presents the origins and evolution of the systems engineering discipline and helps readers gain a personal familiarity with systems engineering experts: their experience, opinions and attitudes in this field This book is based on a qualitative study that includes dozens of in-depth interviews with experts in the systems engineering field. This book is broken into three main parts. The first part is a general overview of the systems engineering field. The second part discusses the changes the systems engineering discipline has undergone with the analysis as case studies of two significant Israeli defence systems projects: the IAI Lavi project and the Iron Dome project. The third part of this book contains interviews with renowned experts in the systems engineering field. This part is divided into five sections: systems engineering as the answer to the challenges of a complex technological world – the aerospace industries; the development of systems engineering in the commercial and industrial worlds, and in complex civil systems; the impact of the accelerated development of the computing world on systems engineering processes; systems engineering and the academic world; and systems engineering in the world of training and consulting. This book presents the main insights derived from the interviews, and an analysis and discussion of the question of the relevance of systems engineering to the management world. Some highlights of this book are that it Integrates the technological aspects with the behavioural aspects of the field Serves managerial needs of engineering and management in general, so managers with no technical background can derive knowledge from this book Provides approaches for seeing beyond technology-understanding the mission Managing and Engineering Complex Technological Systems is a great resource on management for managers as well as systems engineers.

This book presents results of projects carried out by both scientific and industry researchers into the techniques to help in maintenance, control, supervision and security of systems, taking into account the technical environmental and human factors. This work is supported by the Scientific Group GIS 3SGS. It is a collaborative work from 13 partners (academic and industrial) who have come together to deal with security problems. The problems and techniques discussed mainly focus on stochastic and dynamic modeling, maintenance, forecasting, diagnosis, reliability, performance, organizational, human and environmental factors, uncertainty and experience feedback. Part 1. Industrial Issues 1. Safety and Performance of Electricity Production Facilities, Gilles Deleuze, Jean Primet, Philippe Klein, Carole Duval and Antoine Despujols. 2. Monitoring of Radioactive Waste Disposal Cells in Deep Geological Formation, St?phane Buschaert and Sylvie Lesoille. 3. Towards Fourth-generation Nuclear Reactors, Jean-Philippe Nabot, Olivier Gastaldi, Fran?ois Baqu?, K?vin Paumel and Jean-Philippe Jeannot. Part 2. Supervison and Modeling of Complex Systems 4. Fault-tolerant Data-fusion Method: Application on Platoon Vehicle Localization, Maan El Badaoui El Najiar, Cherif Smaili, Fran?ois Charpillet, Denis Pomorski and Mireille Bayart. 5. Damage and Forecast Modeling, Anne Barros, Eric Levrat, Mitra Fouladirad, Khanh Le Son, Thomas Ruin, Beno?t Iung, Alexandre Voisin, Maxime Monnin, Antoine Despujols, Emmanuel R?my and Ludovic B?n?trix. 6. Diagnosis of Systems with Multiple Operating Modes, Taha Boukhobza, Fr?d?ric Hamelin, Beno?t Marx, Gilles Mourot, Anca Maria Nagy, Jos? Ragot, Djemal Eddine Chouaib Belkhiat, Kevin Guelton, Dalel Jabri, Noureddine Manamanni, Sinuh? Martinez, Nadhir Messai, Vincent Cocquempot, Assia Hakem, Komi Midzodzi Pekpe, Talel Zouari, Michael Defoort, Mohammed Djemai and J?r?my Van Gorp. 7. Multitask Learning for the Diagnosis of Machine Fleet, Xiyan He, Gilles Mourot, Didier Maquin, Jos? Ragot, Pierre Beauseroy, Andr? Smolarz and Edith Grall-Ma?s. 8. The APPRODYN Project: Dynamic Reliability Approaches to Modeling Critical Systems, Jean-Fran?ois Aubry, Genia Babykina, Nicolae Brinzei, Slimane Medjaher, Anne Barros, Christophe Berenguer, Antoine Grall, Yves Langeron, Danh Ngoc Nguyen, Gilles Deleuze, Beno?te De Saporta, Fran?ois Dufour and Huilong Zhang. Part 3. Characterizing Background Noise, Identifying Characteristic Signatures in Test Cases and Detecting Noise Reactors 9. Aims, Context and Type of Signals Studied, Fran?ois Baqu?, Olivier Descombin, Olivier Gastaldi and Yves Vandenboomgaerde. 10. Detection/Classification of Argon and Water Injections into Sodium into an SG of a Fast Neutron Reactor, Pierre Beauseroy, Edith Grall-Ma?s and Igor Nikiforov. 11. A Dynamic Learning-based Approach to the Surveillance and Monitoring of Steam Generators in Prototype Fast Reactors, Laurent Hartert, Moamar Sayed-Mouchaweh and Danielle Nuzillard. 12. SVM Time-Frequency Classification for the Detection of Injection States, Simon Henrot, El-Hadi Djermoune and David Brie. 13. Time and Frequency Domain Approaches for the Characterization of Injection States, Jean-Philippe Cassar and Komi Midzodzi Pekpe. Part 4. Human, Organizational and Environmental Factors in Risk Analysis 14. Risk Analysis and Management in Systems Integrating Technical, Human, Organizational and Environmental Aspects, Geoffrey Fallet-Fidry, Carole Duval, Christophe Simon, Eric Levrat, Philippe Weber and Beno?t Iung. 15. Integrating Human and Organizational Factors into the BCD Risk Analysis Model: An Influence Diagram-based approach, Karima Sedki,

Computer modeling and simulation (M&S) allows engineers to study and analyze complex systems. Discrete-event system (DES)-M&S is used in modern management, industrial engineering, computer science, and the military. As computer speeds and memory capacity increase, so DES-M&S tools become more powerful and more widely used in solving real-life problems. Based on over 20 years of evolution within a classroom environment, as well as on decades-long experience in developing simulation-based solutions for high-tech industries, Modeling and Simulation of Discrete-Event Systems is the only book on DES-M&S in which all the major DES modeling formalisms – activity-based, process-oriented, state-based, and event-based – are covered in a unified manner: A well-defined procedure for building a formal model in the form of event graph, ACD, or state graph Diverse types of modeling templates and examples that can be used as building blocks for a complex, real-life model A systematic, easy-to-follow procedure combined with sample C# codes for developing simulators in various modeling formalisms Simple tutorials as well as sample model files for using popular off-the-shelf simulators such as SIGMA®, ACE®, and Arena® Up-to-date research results as well as research issues and directions in DES-M&S Modeling and Simulation of Discrete-Event Systems is an ideal textbook for undergraduate and graduate students of simulation/industrial engineering and computer science, as well as for simulation practitioners and researchers.

This book introduces the state-of-the-art in research in parallel and distributed embedded systems, which have been enabled by developments in silicon technology, micro-electro-mechanical systems (MEMS), wireless communications, computer networking, and digital electronics. These systems have diverse applications in domains including military and defense, medical, automotive, and unmanned autonomous vehicles. The emphasis of the book is on the modeling and optimization of emerging parallel and distributed embedded systems in relation to the three key design metrics of performance, power and dependability. Key features: Includes an embedded wireless sensor networks case study to help illustrate the modeling and optimization of distributed embedded systems. Provides an analysis of multi-core/many-core based embedded systems to explain the modeling and optimization of parallel embedded systems. Features an application metrics estimation model; Markov modeling for fault tolerance and analysis; and queueing theoretic modeling for performance evaluation. Discusses optimization approaches for distributed wireless sensor networks; high-performance and energy-efficient techniques at the architecture, middleware and software levels for parallel multicore-based embedded systems; and dynamic optimization methodologies. Highlights research challenges and future research directions. The book is primarily aimed at researchers in embedded systems; however, it will also serve as an invaluable reference to senior undergraduate and graduate students with an interest in embedded systems research.

The emergence of social networks, OpenCourseWare, Massive Open Online Courses, informal remote learning and connectivist approaches to learning has made the analysis and evaluation of Digital Learning Environments more complex. Modeling these complex systems makes it possible to transcribe the phenomena observed and facilitates the study of these processes with the aid of specific tools. Once this essential step is taken, it then becomes possible to develop plausible scenarios from the observation of emerging phenomena and dominant trends. This book highlights the contribution of complex systems theory in the study of next generation Digital Learning Environments. It describes a realistic approach and proposes a range of effective management tools to achieve it.

This book is a general presentation of complex systems, examined from the point of view of management. There is no standard formula to govern such systems, nor to effectively understand and respond to them. The interdisciplinary theory of self-organization is teeming with examples of living systems that can reorganize at a higher level of complexity when confronted with an external challenge of a certain magnitude. Modern businesses, considered as complex systems, ideally know how to flexibly and resiliently adapt to their environment, and also how to prepare for change via self-organization. Understanding sources of potential crisis is essential for leaders, though not all crises are necessarily bad news, as creative firms know how to respond to challenges through innovation: new products and markets, organizational learning for collective intelligence, and more.