Performance Evaluation Of Industrial Systems

Author: David Elizandro
Publisher: CRC Press
ISBN: 1439871345
Size: 76.71 MB
Format: PDF, Kindle
View: 1447
Download
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.

Simulation Of Industrial Systems

Author: David Elizandro
Publisher: Auerbach Publications
ISBN: 9781420067446
Size: 76.50 MB
Format: PDF, Docs
View: 1193
Download
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 how to model traditional applications to optimize production operations, Simulation of Industrial Systems: Discrete Event Simulation Using Excel/VBA— · Introduces the Design Environment for Event Driven Simulation (DEEDS), an original simulator, which facilitates the modeling of complex situations using four (self-contained) nodes: source, queue, facility, and delay. · Demonstrates how to use discrete event simulation as a powerful tool for the analysis, planning, design, and operation of diverse production systems · Shows how to model application areas such as facilities layout, material handling, inventory control, scheduling, maintenance, quality control, and supply chain logistics · Integrates the design of experiments and optimization techniques for improving production systems With the comprehensive instruction provided within these pages, in combination with the flexibility of the DEEDS program environment, operations managers will be able to harness the power of discrete event simulation to streamline their production environments. The authors have created a website with a variety of teaching aids that professors will be able to access

Simulation Modeling And Analysis With Arena

Author: Tayfur Altiok
Publisher: Elsevier
ISBN: 9780080548951
Size: 13.11 MB
Format: PDF, ePub, Mobi
View: 1261
Download
Simulation Modeling and Analysis with Arena is a highly readable textbook which treats the essentials of the Monte Carlo discrete-event simulation methodology, and does so in the context of a popular Arena simulation environment. It treats simulation modeling as an in-vitro laboratory that facilitates the understanding of complex systems and experimentation with what-if scenarios in order to estimate their performance metrics. The book contains chapters on the simulation modeling methodology and the underpinnings of discrete-event systems, as well as the relevant underlying probability, statistics, stochastic processes, input analysis, model validation and output analysis. All simulation-related concepts are illustrated in numerous Arena examples, encompassing production lines, manufacturing and inventory systems, transportation systems, and computer information systems in networked settings. · Introduces the concept of discrete event Monte Carlo simulation, the most commonly used methodology for modeling and analysis of complex systems · Covers essential workings of the popular animated simulation language, ARENA, including set-up, design parameters, input data, and output analysis, along with a wide variety of sample model applications from production lines to transportation systems · Reviews elements of statistics, probability, and stochastic processes relevant to simulation modeling * Ample end-of-chapter problems and full Solutions Manual * Includes CD with sample ARENA modeling programs

Simulation Modeling And Arena

Author: Manuel D. Rossetti
Publisher: John Wiley & Sons
ISBN: 111885814X
Size: 22.88 MB
Format: PDF, Mobi
View: 6739
Download
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.

Simulation Modeling With Simio

Author: Jeffrey Allen Joines
Publisher: Createspace Independent Publishing Platform
ISBN: 9781519142207
Size: 71.94 MB
Format: PDF
View: 263
Download
This workbook features a participatory style of learning. You don't sit and read the book without a computer loaded with SIMIO. We expect your active participation in using SIMIO as you turn the pages. We try to carry on a conversation with you. Our belief is that simulation is not a spectator sport. This edition of the workbook has an evolved structure based on use and experience. More emphasis is placed on "why" modeling choices are made, to supplement the "how" in using SIMIO in simulation. In Chapter 1, we present fundamental simulation concepts, independent of SIMIO which can be skipped for those who already understand these fundamentals. In Chapters 2 through 6, concentrates of the use of the Standard Library Objects in SIMIO. You can do a lot of simulation modeling without resorting to more complex concepts. A key part of those chapters is learning to identify/separate the data in a model from the model structure. Chapter 7 introduces the fundamental topic of "processes," which we frequently employ in the following chapters. Chapters 8 and 9 concentrate on the important topics of flow and capacity. Chapter 10 introduces optimization in the context of supply chain modeling. Chapter 11 presents the influence of bias and variability on terminating and steady-state simulation. Chapter 12 introduces SIMIO materials handling features. Chapter 13 extends the use of resources while Chapters 14 and 15 describes the use of workers including the detailed services provided by task sequences and their animation. Chapter 16 details the simulation of call centers with reneging, balking, and cost optimization. Chapters 17 through 20 presents object-oriented simulation capabilities in SIMIO. Chapter 17 builds a model out of an existing model (we call it sub-modeling). Chapter 18 describes the anatomy of an existing SIMIO and in Chapter 19 we build a new object by "sub-classing" an existing object. In Chapter 20 a new object is designed and built from a base SIMIO object and its creation is contrasted with standard SIMIO object. Chapter 21 presents some of the continuous modeling features in SIMIO. Chapters 22 and 23 demonstrates the power of object-oriented simulation in the modeling supply chains and process planning respectively. We include an appendix on input modeling, although SIMIO does not provide software. The book is designed to be read from chapter to chapter, although it is possible to pick out certain concepts and topics. Some redundancy is helpful in learning. By the time you have finished this book you should be well-prepared to build models in SIMIO and to understand the virtues of different modeling approaches. Like SIMIO itself, this workbook has been designed for a variety of student, teacher, and practitioner audiences. For example, if you are interested in manufacturing, you will want to be sure to study data-based modeling in Chapter 5, assemply and packaging in Chapter 6, the workstation in Chapter 9, and material handling in Chapter 12. If you are interested in logistics, don't miss modeling of distances in Chapter 3, flow and capacity in Chapter 8, inventories and supply chains in Chapter 10, and free space travel in Chapter12. If you are interested in healthcare, be sure to review scheduled arrivals in Chapter 8, resource decision making in Chapter 13, mobile workers in Chapter 14, and animated people and task sequences in Chapter 15. If object-oreinted simulation is your interest, make sure to study Chapters 17 through 20, which describes how SIMIO provides composition and inheritance to create objects. Manufacting examples and examples from the service sector are used throughout. Also we pay some attention to input modeling (including input sensitivity) and output analysis (including confidence intervals and optimization). This workbook provides comprehensive and in-depth discussion of simulation modeling with SIMIO.

Production And Operations Management Systems

Author: Sushil Gupta
Publisher: CRC Press
ISBN: 1466507330
Size: 61.87 MB
Format: PDF, Kindle
View: 7513
Download
Since the beginning of mankind on Earth, if the "busyness" process was successful, then some form of benefit sustained it. The fundamentals are obvious: get the right inputs (materials, labor, money, and ideas); transform them into highly demanded, quality outputs; and make it available in time to the end consumer. Illustrating how operations relate to the rest of the organization, Production and Operations Management Systems provides an understanding of the production and operations management (P/OM) functions as well as the processes of goods and service producers. The modular character of the text permits many different journeys through the materials. If you like to start with supply chain management (Chapter 9) and then move on to inventory management (Chapter 5) and then quality management (Chapter 8), you can do so in that order. However, if your focus is product line stability and quick response time to competition, you may prefer to begin with project management (Chapter 7) to reflect the continuous project mode required for fast redesign rapid response. Slides, lectures, Excel worksheets, and solutions to short and extended problem sets are available on the Downloads / Updates tabs. The project management component of P/OM is no longer an auxiliary aspect of the field. The entire system has to be viewed and understood. The book helps students develop a sense of managerial competence in making decisions in the design, planning, operation, and control of manufacturing, production, and operations systems through examples and case studies. The text uses analytical techniques when necessary to develop critical thinking and to sharpen decision-making skills. It makes production and operations management (P/OM) interesting, even exciting, to those who are embarking on a career that involves business of any kind.

Modeling And Simulation Fundamentals

Author: John A. Sokolowski
Publisher: John Wiley & Sons
ISBN: 9780470590614
Size: 51.50 MB
Format: PDF, ePub
View: 458
Download
An insightful presentation of the key concepts, paradigms, and applications of modeling and simulation Modeling and simulation has become an integral part of research and development across many fields of study, having evolved from a tool to a discipline in less than two decades. Modeling and Simulation Fundamentals offers a comprehensive and authoritative treatment of the topic and includes definitions, paradigms, and applications to equip readers with the skills needed to work successfully as developers and users of modeling and simulation. Featuring contributions written by leading experts in the field, the book's fluid presentation builds from topic to topic and provides the foundation and theoretical underpinnings of modeling and simulation. First, an introduction to the topic is presented, including related terminology, examples of model development, and various domains of modeling and simulation. Subsequent chapters develop the necessary mathematical background needed to understand modeling and simulation topics, model types, and the importance of visualization. In addition, Monte Carlo simulation, continuous simulation, and discrete event simulation are thoroughly discussed, all of which are significant to a complete understanding of modeling and simulation. The book also features chapters that outline sophisticated methodologies, verification and validation, and the importance of interoperability. A related FTP site features color representations of the book's numerous figures. Modeling and Simulation Fundamentals encompasses a comprehensive study of the discipline and is an excellent book for modeling and simulation courses at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the fields of computational statistics, engineering, and computer science who use statistical modeling techniques.

A Guide To Simulation

Author: P. Bratley
Publisher: Springer Science & Business Media
ISBN: 146840167X
Size: 77.27 MB
Format: PDF, ePub
View: 628
Download
Simulation means driving a model of a system with suitable inputs and observing the corresponding outputs. It is widely applied in engineering, in business, and in the physical and social sciences. Simulation method ology araws on computer. science, statistics, and operations research and is now sufficiently developed and coherent to be called a discipline in its own right. A course in simulation is an essential part of any operations re search or computer science program. A large fraction of applied work in these fields involves simulation; the techniques of simulation, as tools, are as fundamental as those of linear programming or compiler construction, for example. Simulation sometimes appears deceptively easy, but perusal of this book will reveal unexpected depths. Many simulation studies are statistically defective and many simulation programs are inefficient. We hope that our book will help to remedy this situation. It is intended to teach how to simulate effectively. A simulation project has three crucial components, each of which must always be tackled: (1) data gathering, model building, and validation; (2) statistical design and estimation; (3) programming and implementation. Generation of random numbers (Chapters 5 and 6) pervades simulation, but unlike the three components above, random number generators need not be constructed from scratch for each project. Usually random number packages are available. That is one reason why the chapters on random numbers, which contain mainly reference material, follow the ch!lPters deal ing with experimental design and output analysis.

Financial Simulation Modeling In Excel

Author: Keith A. Allman
Publisher: John Wiley & Sons
ISBN: 1118137221
Size: 30.99 MB
Format: PDF, Docs
View: 5844
Download
"I've worked with simulation in business for over 20 years, and Allman really nails it with this book. I admit that I own his previous book on structured finance cash flows, but I was surprised by what I found in here. He addresses the fundamental questions of how decision makers react to simulations and his read was very much in accordance with what I've experienced myself. When it came to the nuts and bolts of describing the different types of simulation analysis the book becomes incredibly detailed. There is working code and models for a fantastic array of the most common simulation problems. If you're so inclined, the book very carefully steps through the tricky math needed to really understand the theory behind stochastic modeling in finance. If you're preparing models that include any kind of randomization or stochastic modeling component, this book is a must-read, a tremendous value and time-saver." — David Brode of The Brode Group A practical guide to understanding and implementing financial simulation modeling As simulation techniques become more popular among the financial community and a variety of sub-industries, a thorough understanding of theory and implementation is critical for practitioners involved in portfolio management, risk management, pricing, and capital budgeting. Financial Simulation Modeling in Excel contains the information you need to make the most informed decisions possible in your professional endeavors. Financial Simulation Modeling in Excel contains a practical, hands-on approach to learning complex financial simulation methodologies using Excel and VBA as a medium. Crafted in an easy to understand format, this book is suitable for anyone with a basic understanding of finance and Excel. Filled with in-depth insights and expert advice, each chapter takes you through the theory behind a simulation topic and the implementation of that same topic in Excel/VBA in a step-by-step manner. Organized in an easy-to-follow fashion, this guide effectively walks you through the process of creating and implementing risk models in Excel A companion website contains all the Excel models risk experts and quantitative analysts need to practice and confirm their results as they progress Keith Allman is the author of other successful modeling books, including Corporate Valuation Modeling and Modeling Structured Finance Cash Flows with Microsoft Excel Created for those with some background in finance and experience in Excel, this reliable resource shows you how to effectively perform sound financial simulation modeling, even if you've yet to do extensive modeling up to this point in your professional or academic career.

Foundations And Methods Of Stochastic Simulation

Author: Barry Nelson
Publisher: Springer Science & Business Media
ISBN: 146146160X
Size: 69.51 MB
Format: PDF, ePub, Docs
View: 520
Download
This graduate-level text covers modeling, programming and analysis of simulation experiments and provides a rigorous treatment of the foundations of simulation and why it works. It introduces object-oriented programming for simulation, covers both the probabilistic and statistical basis for simulation in a rigorous but accessible manner (providing all necessary background material); and provides a modern treatment of experiment design and analysis that goes beyond classical statistics. The book emphasizes essential foundations throughout, rather than providing a compendium of algorithms and theorems and prepares the reader to use simulation in research as well as practice. The book is a rigorous, but concise treatment, emphasizing lasting principles but also providing specific training in modeling, programming and analysis. In addition to teaching readers how to do simulation, it also prepares them to use simulation in their research; no other book does this. An online solutions manual for end of chapter exercises is also be provided.​