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.
Computer simulation is the key to comprehending and controlling the full-scale industrial plant used in the chemical, oil, gas and electrical power industries. Simulation of Industrial Processes for Control Engineers shows how to use the laws of physics and chemistry to produce the equations to simulate dynamically all the most important unit operations found in process and power plant.The book explains how to model chemical reactors, nuclear reactors, distillation columns, boilers, deaerators, refrigeration vessels, storage vessels for liquids and gases, liquid and gas flow through pipes and pipe networks, liquid and gas flow through installed control valves, control valve dynamics (including nonlinear effects such as static friction), oil and gas pipelines, heat exchangers, steam and gas turbines, compressors and pumps, as well as process controllers (including three methods of integral desaturation). The phenomenon of markedly different time responses ("stiffness") is considered and various ways are presented to get around the potential problem of slow execution time. The book demonstrates how linearization may be used to give a diverse check on the correctness of the as-programmed model and explains how formal techniques of model validation may be used to produce a quantitative check on the simulation model's overall validity.The material is based on many years' experience of modelling and simulation in the chemical and power industries, supplemented in recent years by university teaching at the undergraduate and postgraduate level. Several important new results are presented. The depth is sufficient to allow real industrial problems to be solved, thus making the book attractive to engineers working in industry. But the book's step-by-step approach makes the text appropriate also for post-graduate students of control engineering and for undergraduate students in electrical, mechanical and chemical engineering who are studying process control in their second year or later.
Basic approaches to discrete simulation have been process simulation languages (e.g., GPSS) and event-scheduling type (e.g., SIMSCRIPT). The trade-offs are that event-scheduling languages offer more modeling flexibility and process-oriented languages are more intuitive to the user. With these considerations in mind, authors David Elizandro and Hamdy Taha embarked on the development of a new discrete simulation environment that is easy to use, yet flexible enough to model complex production systems. They introduced this environment, Design Environment for Event Driven Simulation (DEEDS), in Simulation of Industrial Systems: Discrete Event Simulation in Using Excel/VBA. The DEEDS environment is itself an Excel/VBA add-in. Based on this foundation, the second edition, now titled Performance Evaluation of Industrial Systems: Discrete Event Simulation in Using Excel/VBA incorporates the use of discrete simulation to statistically analyze a system and render the most efficient time sequences, designs, upgrades, and operations. This updated edition includes new visualization graphics for DEEDS software, improvements in the optimization of the simulation algorithms, a new chapter on queuing models, and an Excel 2007 version of the DEEDS software. Organized into three parts, the book presents concepts of discrete simulation, covers DEEDS, and discusses a variety of applications using DEEDS. The flexibility of DEEDS makes it a great tool for students or novices to learn concepts of discrete simulation and this book can form the basis of an introductory undergraduate course on simulation. The expanded depth of coverage in the second edition gives it a richness other introductory texts do not have and provides practitioners a reference for their simulation projects. It may also be used as a research tool by faculty and graduate students who are interested in "optimizing" production systems.
In any production environment, discrete event simulation is a powerful tool for the analysis, planning, and operating of a manufacturing facility. Operations managers can use simulation to improve their production systems by eliminating bottlenecks, reducing cycle time and cost, and increasing capacity utilization. Offering a hands-on tutorial on h
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.
One critical barrier leading to successful implementation of flexible manufacturing and related automated systems is the ever-increasing complexity of their modeling, analysis, simulation, and control. Research and development over the last three decades has provided new theory and graphical tools based on Petri nets and related concepts for the design of such systems. The purpose of this book is to introduce a set of Petri-net-based tools and methods to address a variety of problems associated with the design and implementation of flexible manufacturing systems (FMSs), with several implementation examples.There are three ways this book will directly benefit readers. First, the book will allow engineers and managers who are responsible for the design and implementation of modern manufacturing systems to evaluate Petri nets for applications in their work. Second, it will provide sufficient breadth and depth to allow development of Petri-net-based industrial applications. Third, it will allow the basic Petri net material to be taught to industrial practitioners, students, and academic researchers much more efficiently. This will foster further research and applications of Petri nets in aiding the successful implementation of advanced manufacturing systems.
Emphasizes a hands-on approach to learning statistical analysis and model building through the use of comprehensive examples, problems sets, and software applications With a unique blend of theory and applications, Simulation Modeling and Arena®, Second Edition integrates coverage of statistical analysis and model building to emphasize the importance of both topics in simulation. Featuring introductory coverage on how simulation works and why it matters, the Second Edition expands coverage on static simulation and the applications of spreadsheets to perform simulation. The new edition also introduces the use of the open source statistical package, R, for both performing statistical testing and fitting distributions. In addition, the models are presented in a clear and precise pseudo-code form, which aids in understanding and model communication. Simulation Modeling and Arena, Second Edition also features: Updated coverage of necessary statistical modeling concepts such as confidence interval construction, hypothesis testing, and parameter estimation Additional examples of the simulation clock within discrete event simulation modeling involving the mechanics of time advancement by hand simulation A guide to the Arena Run Controller, which features a debugging scenario New homework problems that cover a wider range of engineering applications in transportation, logistics, healthcare, and computer science A related website with an Instructor’s Solutions Manual, PowerPoint® slides, test bank questions, and data sets for each chapter Simulation Modeling and Arena, Second Edition is an ideal textbook for upper-undergraduate and graduate courses in modeling and simulation within statistics, mathematics, industrial and civil engineering, construction management, business, computer science, and other departments where simulation is practiced. The book is also an excellent reference for professionals interested in mathematical modeling, simulation, and Arena.
Since the publication of the first edition in 1982, the goal of Simulation Modeling and Analysis has always been to provide a comprehensive, state-of-the-art, and technically correct treatment of all important aspects of a simulation study. The book strives to make this material understandable by the use of intuition and numerous figures, examples, and problems. It is equally well suited for use in university courses, simulation practice, and self study. The book is widely regarded as the “bible” of simulation and now has more than 100,000 copies in print. The book can serve as the primary text for a variety of courses; for example: • A first course in simulation at the junior, senior, or beginning-graduate-student level in engineering, manufacturing, business, or computer science (Chaps. 1 through 4, and parts of Chaps. 5 through 9). At the end of such a course, the students will be prepared to carry out complete and effective simulation studies, and to take advanced simulation courses. • A second course in simulation for graduate students in any of the above disciplines (most of Chaps. 5 through 12). After completing this course, the student should be familiar with the more advanced methodological issues involved in a simulation study, and should be prepared to understand and conduct simulation research. • An introduction to simulation as part of a general course in operations research or management science (part of Chaps. 1, 3, 5, 6, and 9).
This book has been written for all those interested in flexible manufacturing systems (FMS) and other forms of computerized manufacturing systems (CMS). It deals with many aspects of the design, operation, and simulation of FMS and explains the origins of FMS.
A complete introduction to the field of discrete simulation; examining both the generic background material necessary to perform any simulation project and complete documentation for the new network-based simulation language SIMNET.