Industrial Robustness
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| Author | : Anand M. Joglekar |
| Publisher | : John Wiley & Sons |
| Total Pages | : 283 |
| Release | : 2010-04-30 |
| Genre | : Science |
| ISBN | : 0470584122 |
HELPS YOU FULLY LEVERAGE STATISTICAL METHODS TO IMPROVE INDUSTRIAL PERFORMANCE Industrial Statistics guides you through ten practical statistical methods that have broad applications in many different industries for enhancing research, product design, process design, validation, manufacturing, and continuous improvement. As you progress through the book, you'll discover some valuable methods that are currently underutilized in industry as well as other methods that are often not used correctly. With twenty-five years of teaching and consulting experience, author Anand Joglekar has helped a diverse group of companies reduce costs, accelerate product development, and improve operations through the effective implementation of statistical methods. Based on his experience working with both clients and students, Dr. Joglekar focuses on real-world problem-solving. For each statistical method, the book: Presents the most important underlying concepts clearly and succinctly Minimizes mathematical details that can be delegated to a computer Illustrates applications with numerous practical examples Offers a "Questions to Ask" section at the end of each chapter to assist you with implementation The last chapter consists of 100 practical questions followed by their answers. If you're already familiar with statistical methods, you may want to take the test first to determine which methods to focus on. By helping readers fully leverage statistical methods to improve industrial performance, this book becomes an ideal reference and self-study guide for scientists, engineers, managers and other technical professionals across a wide range of industries. In addition, its clear explanations and examples make it highly suited as a textbook for undergraduate and graduate courses in statistics.
| Author | : Richard H. Baltz |
| Publisher | : American Society for Microbiology Press |
| Total Pages | : 1894 |
| Release | : 2010-03-25 |
| Genre | : Medical |
| ISBN | : 155581512X |
A rich array of methods and discussions of productive microbial processes. • Reviews of the newest techniques, approaches, and options in the use of microorganisms and other cell culture systems for the manufacture of pharmaceuticals, industrial enzymes and proteins, foods and beverages, fuels and fine chemicals, and other products. • Focuses on the latest advances and findings on the current state of the art and science and features a new section on the microbial production of biofuels and fine chemicals, as well as a stronger emphasis on mammalian cell culture methods. • Covers new methods that enhance the capacity of microbes used for a wide range of purposes, from winemaking to pharmaceuticals to bioremediation, at volumes from micro- to industrial scale.
| Author | : Michael J. Grimble |
| Publisher | : |
| Total Pages | : 624 |
| Release | : 1994 |
| Genre | : Technology & Engineering |
| ISBN | : |
| Author | : Michael J. Grimble |
| Publisher | : John Wiley & Sons |
| Total Pages | : 712 |
| Release | : 2006-05-18 |
| Genre | : Science |
| ISBN | : |
Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems presents a comprehensive introduction to the use of frequency domain and polynomial system design techniques for a range of industrial control and signal processing applications. The solution of stochastic and robust optimal control problems is considered, building up from single-input problems and gradually developing the results for multivariable design of the later chapters. In addition to cataloguing many of the results in polynomial systems needed to calculate industrial controllers and filters, basic design procedures are also introduced which enable cost functions and system descriptions to be specified in order to satisfy industrial requirements. Providing a range of solutions to control and signal processing problems, this book: Presents a comprehensive introduction to the polynomial systems approach for the solution of H2 and H∞ optimal control problems. Develops robust control design procedures using frequency domain methods. Demonstrates design examples for gas turbines, marine systems, metal processing, flight control, wind turbines, process control and manufacturing systems. Includes the analysis of multi-degrees of freedom controllers and the computation of restricted structure controllers that are simple to implement. Considers time-varying control and signal processing problems. Addresses the control of non-linear processes using both multiple model concepts and new optimal control solutions. Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems is essential reading for professional engineers requiring an introduction to optimal control theory and insights into its use in the design of real industrial processes. Students and researchers in the field will also find it an excellent reference tool.
| Author | : Tie Qiu |
| Publisher | : Springer Nature |
| Total Pages | : 224 |
| Release | : 2022-06-11 |
| Genre | : Computers |
| ISBN | : 9811696098 |
The IoT topology defines the way various components communicate with each other within a network. Topologies can vary greatly in terms of security, power consumption, cost, and complexity. Optimizing the IoT topology for different applications and requirements can help to boost the network’s performance and save costs. More importantly, optimizing the topology robustness can ensure security and prevent network failure at the foundation level. In this context, this book examines the optimization schemes for topology robustness in the IoT, helping readers to construct a robustness optimization framework, from self-organizing to intelligent networking. The book provides the relevant theoretical framework and the latest empirical research on robustness optimization of IoT topology. Starting with the self-organization of networks, it gradually moves to genetic evolution. It also discusses the application of neural networks and reinforcement learning to endow the node with self-learning ability to allow intelligent networking. This book is intended for students, practitioners, industry professionals, and researchers who are eager to comprehend the vulnerabilities of IoT topology. It helps them to master the research framework for IoT topology robustness optimization and to build more efficient and reliable IoT topologies in their industry.
| Author | : Shaul Salomon |
| Publisher | : Springer |
| Total Pages | : 194 |
| Release | : 2019-07-06 |
| Genre | : Technology & Engineering |
| ISBN | : 303015050X |
This book presents a novel framework, known as Active Robust Optimization, which provides the tools for evaluating, comparing and optimizing changeable products. Since any product that can change its configuration during normal operation may be considered a “changeable product,” the framework is widely applicable. Further, the methodology enables designers to use adaptability to deal with uncertainties and so avoid over-conservative designs. Offering a comprehensive overview of the framework, including its unique features, such as its ability to optimally respond to uncertain situations, the book also defines a new class of optimization problem and examines the effects of changes in various parameters on their solution. Lastly, it discusses innovative approaches for solving the problem and demonstrates these with two examples from different fields in engineering design: optimization of an optical table and optimization of a gearbox.
| Author | : Michael J. Grimble |
| Publisher | : John Wiley & Sons |
| Total Pages | : 698 |
| Release | : 2006-05-01 |
| Genre | : Science |
| ISBN | : 0470020741 |
Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems presents a comprehensive introduction to the use of frequency domain and polynomial system design techniques for a range of industrial control and signal processing applications. The solution of stochastic and robust optimal control problems is considered, building up from single-input problems and gradually developing the results for multivariable design of the later chapters. In addition to cataloguing many of the results in polynomial systems needed to calculate industrial controllers and filters, basic design procedures are also introduced which enable cost functions and system descriptions to be specified in order to satisfy industrial requirements. Providing a range of solutions to control and signal processing problems, this book: * Presents a comprehensive introduction to the polynomial systems approach for the solution of H_2 and H_infinity optimal control problems. * Develops robust control design procedures using frequency domain methods. * Demonstrates design examples for gas turbines, marine systems, metal processing, flight control, wind turbines, process control and manufacturing systems. * Includes the analysis of multi-degrees of freedom controllers and the computation of restricted structure controllers that are simple to implement. * Considers time-varying control and signal processing problems. * Addresses the control of non-linear processes using both multiple model concepts and new optimal control solutions. Robust Industrial Control Systems: Optimal Design Approach for Polynomial Systems is essential reading for professional engineers requiring an introduction to optimal control theory and insights into its use in the design of real industrial processes. Students and researchers in the field will also find it an excellent reference tool.
| Author | : Ralph Langner |
| Publisher | : Momentum Press |
| Total Pages | : 358 |
| Release | : 2011-09-15 |
| Genre | : Computers |
| ISBN | : 1606503022 |
From the researcher who was one of the first to identify and analyze the infamous industrial control system malware "Stuxnet," comes a book that takes a new, radical approach to making Industrial control systems safe from such cyber attacks: design the controls systems themselves to be "robust." Other security experts advocate risk management, implementing more firewalls and carefully managing passwords and access. Not so this book: those measures, while necessary, can still be circumvented. Instead, this book shows in clear, concise detail how a system that has been set up with an eye toward quality design in the first place is much more likely to remain secure and less vulnerable to hacking, sabotage or malicious control. It blends several well-established concepts and methods from control theory, systems theory, cybernetics and quality engineering to create the ideal protected system. The book's maxim is taken from the famous quality engineer William Edwards Deming, "If I had to reduce my message to management to just a few words, I'd say it all has to do with reducing variation." Highlights include: - An overview of the problem of "cyber fragility" in industrial control systems - How to make an industrial control system "robust," including principal design objectives and overall strategic planning - Why using the methods of quality engineering like the Taguchi method, SOP and UML will help to design more "armored" industrial control systems.
| Author | : T. RAMAYAH; PUI MUN LEE; EDWARD H. K. NG. |
| Publisher | : Springer Nature |
| Total Pages | : 681 |
| Release | : 2024 |
| Genre | : |
| ISBN | : 2384762575 |
| Author | : Miro Kraetzl |
| Publisher | : World Scientific Publishing Company |
| Total Pages | : 337 |
| Release | : 1999-02-01 |
| Genre | : Technology & Engineering |
| ISBN | : 981310533X |
Nonlinearities exist in all process control systems. The use of linear control techniques is valid only in a narrow region of operation. Nonlinear control is central to future industrial development. In this book, multivariable nonlinear control techniques based on differential geometry are considered in a pragmatic manner. The book provides a simplified and systematic approach to geometric nonlinear control theory. A case study of an industrial evaporator is used as an example throughout the entire book. Various other examples are also used throughout the text to illustrate the theory. The book successfully demonstrates the superiority and simplicity of the class of controllers studied through simulations and actual plant implementations. The simulations were done using the symbolic computation package MAPLE. Discussions are given on the application of symbolic computation in process engineering.This book is aimed at industrial practitioners and postgraduates in engineering, and will be particularly valuable to practicing engineers who find the theory books on control somewhat heavy going. The insights provided in the book will encourage more industrial implementations of nonlinear controllers, and thereby help to bridge the widening gap between control theory and industrial practice.
