This book describes the latest research developments in modeling and simulation in industrial engineering. Topics such as decision and performance analysis and industrial control systems are described. Case studies in industry and services as well as engineering economy and cost estimation are also covered.

This easy to read text provides a broad introduction to the fundamental concepts of modeling and simulation (M&S) and systems engineering, highlighting how M&S is used across the entire systems engineering lifecycle. Features: reviews the full breadth of technologies, methodologies and uses of M&S, rather than just focusing on a specific aspect of the field; presents contributions from specialists in each topic covered; introduces the foundational elements and processes that serve as the groundwork for understanding M&S; explores common methods and methodologies used in M&S; discusses how best to design and execute experiments, covering the use of Monte Carlo techniques, surrogate modeling and distributed simulation; explores the use of M&S throughout the systems development lifecycle, describing a number of methods, techniques, and tools available to support systems engineering processes; provides a selection of case studies illustrating the use of M&S in systems engineering across a variety of domains.

This illuminating text/reference presents a review of the key aspects of the modeling and simulation (M&S) life cycle, and examines the challenges of M&S in different application areas. The authoritative work offers valuable perspectives on the future of research in M&S, and its role in engineering complex systems. Topics and features: reviews the challenges of M&S for urban infrastructure, healthcare delivery, automated vehicle manufacturing, deep space missions, and acquisitions enterprise; outlines research issues relating to conceptual modeling, covering the development of explicit and unambiguous models, communication and decision-making, and architecture and services; considers key computational challenges in the execution of simulation models, in order to best exploit emerging computing platforms and technologies; examines efforts to understand and manage uncertainty inherent in M&S processes, and how these can be unified under a consistent theoretical and philosophical foundation; discusses the reuse of models and simulations to accelerate the simulation model development process. This thought-provoking volume offers important insights for all researchers involved in modeling and simulation across the full spectrum of disciplines and applications, defining a common research agenda to support the entire M&S research community.

This book provides an open platform to establish and share knowledge developed by scholars, scientists, and engineers from all over the world, about various applications of the modeling and simulation in the design process of products, in various engineering fields. The book consists of 12 chapters arranged in two sections (3D Modeling and Virtual Prototyping), reflecting the multidimensionality of applications related to modeling and simulation. Some of the most recent modeling and simulation techniques, as well as some of the most accurate and sophisticated software in treating complex systems, are applied. All the original contributions in this book are jointed by the basic principle of a successful modeling and simulation process: as complex as necessary, and as simple as possible. The idea is to manipulate the simplifying assumptions in a way that reduces the complexity of the model (in order to make a real-time simulation), but without altering the precision of the results.

Model Engineering for Simulation provides a systematic introduction to the implementation of generic, normalized and quantifiable modeling and simulation using DEVS formalism. It describes key technologies relating to model lifecycle management, including model description languages, complexity analysis, model management, service-oriented model composition, quantitative measurement of model credibility, and model validation and verification. The book clearly demonstrates how to construct computationally efficient, object-oriented simulations of DEVS models on parallel and distributed environments. Guides systems and control engineers in the practical creation and delivery of simulation models using DEVS formalism Provides practical methods to improve credibility of models and manage the model lifecycle Helps readers gain an overall understanding of model lifecycle management and analysis Supported by an online ancillary package that includes an instructors and student solutions manual

Advances in computational power have facilitated the development of simulations unprecedented in their computational size, scope of technical issues, spatial and temporal resolution, complexity and comprehensiveness. As a result, complex structures from airplanes to bridges can be almost completely based on model-based simulations. This book gives a state-of-the-art account of modeling and simulation of the life cycle of engineered systems, covering topics of design, fabrication, maintenance and disposal. Providing comprehensive coverage of this rapidly emerging field, Modeling and Simulation-Based Life Cycle Engineering is essential reading for civil, mechanical and manufacturing engineers. It will also appeal to students and academics in this area.

The capability modeling and simulation (M&S) supplies for managing systems complexity and investigating systems behaviors has made it a central activity in the development of new and existing systems. However, a handbook that provides established M&S practices has not been available. Until now. Modeling and Simulation-Based Systems Engineering Handbook details the M&S practices for supporting systems engineering in diverse domains. It discusses how you can identify systems engineering needs and adapt these practices to suit specific application domains, thus avoiding redefining practices from scratch. Although M&S practices are used and embedded within individual disciplines, they are often developed in isolation. However, they address recurring problems common to all disciplines. The editors of this book tackled the challenge by recruiting key representatives from several communities, harmonizing the different perspectives derived from individual backgrounds, and lining them up with the book’s vision. The result is a collection of M&S systems engineering examples that offer an initial means for cross-domain capitalization of the knowledge, methodologies, and technologies developed in several communities. These examples provide the pros and cons of the methods and techniques available, lessons learned, and pitfalls to avoid. As our society moves further in the information era, knowledge and M&S capabilities become key enablers for the engineering of complex systems and systems of systems. Therefore, knowledge and M&S methodologies and technologies become valuable output in an engineering activity, and their cross-domain capitalization is key to further advance the future practices in systems engineering. This book collates information across disciplines to provide you with the tools to more efficiently design and manage complex systems that achieve their goals.