Control charts are widely used in industry to monitor processes that are far from Zero-Defect (ZD), and their use in a near Zero-Defect manufacturing environment poses many problems. This book presents techniques of using control charts for high-quality processes, and some recent findings and applications of statistical control chart techniques for ZD processes are presented.

A powerful technique based on counting of the cumulative conforming (CCC) items between two nonconforming ones is discussed in detail. Extensions of the CCC chart are described, as well as applications of cumulative sum and exponentially weighted moving average techniques to CCC-related data, multivariate methods, economic design of control chart procedures, and modeling and analysis of trended but regularly adjusted processes.

Many examples, charts, and procedures, are presented throughout the book, and references are provided for those interested in exploring the details. A number of questions and issues are posed for further investigations. Researchers and students may find many ideas in this book useful in their academic work, as a foundation is laid for the exploration of many further theoretical and practical issues.

This textbook deals with optimization of dynamic systems. The motivation for undertaking this task is as follows: There is an ever increasing need to produce more efficient, accurate, and lightweight mechanical and electromechanical de vices. Thus, the typical graduating B.S. and M.S. candidate is required to have some familiarity with techniques for improving the performance of dynamic systems. Unfortunately, existing texts dealing with system improvement via optimization remain inaccessible to many of these students and practicing en gineers. It is our goal to alleviate this difficulty by presenting to seniors and beginning graduate students practical efficient techniques for solving engineer ing system optimization problems. The text has been used in optimal control and dynamic system optimization courses at the University of Deleware, the University of Washington and Ohio University over the past four years. The text covers the following material in a straightforward detailed manner: * Static Optimization: The problem of optimizing a function that depends on static variables (i.e., parameters) is considered. Problems with equality and inequality constraints are addressed. * Numerical Methods: Static Optimization: Numerical algorithms for the solution of static optimization problems are presented here. The methods presented can accommodate both the unconstrained and constrained static optimization problems. * Calculus of Variation: The necessary and sufficient conditions for the ex tremum of functionals are presented. Both the fixed final time and free final time problems are considered.

The causes and impacts of power disturbances on both sides of the user-utility interface are discussed, and the results of power quality surveys are reviewed. Desirable attributes of monitoring equipment are discussed along with approaches that can be taken by the electric utilities to improve the quality of the power delivered to customers. Users of sensitive devices, such as computers and health care equipment, are given information on power quality improvement equipment, such as uninterruptible power supplies. Includes a glossary.

STATISTICAL QUALITY CONTROL Provides a basic understanding of statistical quality control (SQC) and demonstrates how to apply the techniques of SQC to improve the quality of products in various sectors This book introduces Statistical Quality Control and the elements of Six Sigma Methodology, illustrating the widespread applications that both have for a multitude of areas, including manufacturing, finance, transportation, and more. It places emphasis on both the theory and application of various SQC techniques and offers a large number of examples using data encountered in real life situations to support each theoretical concept. Statistical Quality Control: Using MINITAB, R, JMP and Python begins with a brief discussion of the different types of data encountered in various fields of statistical applications and introduces graphical and numerical tools needed to conduct preliminary analysis of the data. It then discusses the basic concept of statistical quality control (SQC) and Six Sigma Methodology and examines the different types of sampling methods encountered when sampling schemes are used to study certain populations. The book also covers Phase 1 Control Charts for variables and attributes; Phase II Control Charts to detect small shifts; the various types of Process Capability Indices (CPI); certain aspects of Measurement System Analysis (MSA); various aspects of PRE-control; and more. This helpful guide also Focuses on the learning and understanding of statistical quality control for second and third year undergraduates and practitioners in the field Discusses aspects of Six Sigma Methodology Teaches readers to use MINITAB, R, JMP and Python to create and analyze charts Requires no previous knowledge of statistical theory Is supplemented by an instructor-only book companion site featuring data sets and a solutions manual to all problems, as well as a student book companion site that includes data sets and a solutions manual to all odd-numbered problems Statistical Quality Control: Using MINITAB, R, JMP and Python is an excellent book for students studying engineering, statistics, management studies, and other related fields and who are interested in learning various techniques of statistical quality control. It also serves as a desk reference for practitioners who work to improve quality in various sectors, such as manufacturing, service, transportation, medical, oil, and financial institutions. It's also useful for those who use Six Sigma techniques to improve the quality of products in such areas.

This book presents a collection of real cases from industrial practices that production system and quality managers implement to ensure a high quality as well as a low cost in products. This book is divided in sections that are focused on: * The quality and philosophies implemented to production systems; starting from the product design as well as from the supply system. * The principal statistical techniques applied to the quality assurance (statistical quality control, analysis of tests and failure, quality function deployment, accelerated life tests, among others), the process of gathering information, its validation, its reliability process, and techniques for data analysis. * The techniques applied to the integration of human resources in the process of quality assurance, such as managers and operators' participation, training, and training processes. * Use of information and communications technologies, software, and programs implemented to guarantee the quality of the products in the production systems. ISO standards and policies that are used for quality management and monitoring.

Warranty Data Collection and Analysis deals with warranty data collection and analysis and the problems associated with these activities. The book is a both a research monograph and a handbook for practitioners. As a research monograph, it unifies the literature on warranty data collection and analysis, and presents the important results in an integrated manner. In the process, it highlights topics that require further research. As a handbook, it provides the essential methodology needed by practitioners involved with warranty data collection and analysis, along with extensive references to further results. Models and techniques needed for proper and effective analysis of data are included, together with guidelines for their use in warranty management, product improvement, and new product development. Warranty Data Collection and Analysis will be of interest to researchers (engineers and statisticians) and practitioners (engineers, applied statisticians, and managers) involved with product warranty and reliability. It is also suitable for use as a reference text for graduate-level reliability programs in engineering, applied statistics, operations research, and management.

The global crisis the automotive industry has slipped into over the second half of 2008 has set a fierce spotlight not only on which cars are the right ones to bring to the market but also on how these cars are developed. Be it OEMs developing new models, suppliers integerating themselves deeper into the development processes of different OEMs, analysts estimating economical risks and opportunities of automotive investments, or even governments creating and evaluating scenarios for financial aid for suffering automotive companies: At the end of the day, it is absolutely indispensable to comprehensively understand the processes of auto- tive development - the core subject of this book. Let's face it: More than a century after Carl Benz, Wilhelm Maybach and Gottlieb Daimler developed and produced their first motor vehicles, the overall concept of passenger cars has not changed much. Even though components have been considerably optimized since then, motor cars in the 21st century are still driven by combustion engines that transmit their propulsive power to the road s- face via gearboxes, transmission shafts and wheels, which together with spri- damper units allow driving stability and ride comfort. Vehicles are still navigated by means of a steering wheel that turns the front wheels, and the required control elements are still located on a dashboard in front of the driver who operates the car sitting in a seat.

While books on the medical applications of x-ray imaging exist, there is not one currently available that focuses on industrial applications. Full of color images that show clear spectrometry and rich with applications, X-Ray Imaging fills the need for a comprehensive work on modern industrial x-ray imaging. It reviews the fundamental science of x-ray imaging and addresses equipment and system configuration. Useful to a broad range of radiation imaging practitioners, the book looks at the rapid development and deployment of digital x-ray imaging system.

Industrial development is essential to improvement of the standard of living in all countries. People's health and the environment can be affected, directly or indirectly by routine waste discharges or by accidents. A series of recent major industrial accidents and the effect of pollution highlighted, once again, the need for better management of routine and accidental risks. Moreover, the existence of natural hazards complicate even more the situation in any given region. In the past effort to cope with these risks, if made at all, have been largely on a plant by plant basis; some plants are well equipped to manage environmental and health hazards, while others are not. Managing the hazards of modern technological systems has become a key activity in highly industrialised countries. Decision makers are often confronted with complex issues concerning economic and social development, industrialisation and associated infrastructure needs, population and land use planning. Such issues have to be addressed in such a way that ensures that public health will not be disrupted or substantially degraded. Due to the increasing complexity of technological systems and the higher geographical density of punctual hazard sources, new methodologies and a novel approach to these problems are challenging risk managers and regional planers. Risks from these new complex technological systems are inherently different form those addressed by the risk managers for decades ago.

This book presents the first part of a planned two-volume series devoted to a systematic exposition of some recent developments in the theory of discrete-time Markov control processes (MCPs). Interest is mainly confined to MCPs with Borel state and control (or action) spaces, and possibly unbounded costs and noncompact control constraint sets. MCPs are a class of stochastic control problems, also known as Markov decision processes, controlled Markov processes, or stochastic dynamic pro grams; sometimes, particularly when the state space is a countable set, they are also called Markov decision (or controlled Markov) chains. Regardless of the name used, MCPs appear in many fields, for example, engineering, economics, operations research, statistics, renewable and nonrenewable re source management, (control of) epidemics, etc. However, most of the lit erature (say, at least 90%) is concentrated on MCPs for which (a) the state space is a countable set, and/or (b) the costs-per-stage are bounded, and/or (c) the control constraint sets are compact. But curiously enough, the most widely used control model in engineering and economics--namely the LQ (Linear system/Quadratic cost) model-satisfies none of these conditions. Moreover, when dealing with "partially observable" systems) a standard approach is to transform them into equivalent "completely observable" sys tems in a larger state space (in fact, a space of probability measures), which is uncountable even if the original state process is finite-valued."

In response to the growing importance of power system security and reliability, "Transmission Grid Security" proposes a systematic and probabilistic approach for transmission grid security analysis. The analysis presented uses probabilistic safety assessment (PSA) and takes into account the power system dynamics after severe faults. In the method shown in this book the power system states (stable, not stable, system breakdown, etc.) are connected with the substation reliability model. In this way it is possible to: estimate the system-wide consequences of grid faults; identify a chain of events that might lead to blackout; and rank the importance of different substation components at the system level.

"Transmission Grid Security" also presents the main features and basic mathematics of PSA. It provides the reader with up-to-date knowledge of the regulatory issues affecting the security of transmission grids in Europe.

"Transmission Grid Security" gives a practical method for the security analysis of transmission grids, making it a valuable text for engineers and system operators, as well as postgraduate students. It includes basic information and detailed modules for creating a reliability model that takes into account all the basic operations and components needed after grid faults.

Wavelets: Theory and Applications for Manufacturing presents a systematic description of the fundamentals of wavelet transform and its applications. Given the widespread utilization of rotating machines in modern manufacturing and the increasing need for condition-based, as opposed to fix-interval, intelligent maintenance to minimize machine down time and ensure reliable production, it is of critical importance to advance the science base of signal processing in manufacturing. This volume also deals with condition monitoring and health diagnosis of rotating machine components and systems, such as bearings, spindles, and gearboxes, while also: -Providing a comprehensive survey on wavelets specifically related to problems encountered in manufacturing -Discussing the integration of wavelet transforms with other soft computing techniques such as fuzzy logic, for machine defect and severity classification -Showing how to custom design wavelets for improved performance in signal analysis Focusing on wavelet transform as a tool specifically applied and designed for applications in manufacturing, Wavelets: Theory and Applications for Manufacturing presents material appropriate for both academic researchers and practicing engineers working in the field of manufacturing.

The complete control system engineering solution for continuous and batch manufacturing plants.

This book presents a complete methodology of control system design for continuous and batch manufacturing in such diverse areas as pulp and paper, petrochemical, chemical, food, pharmaceutical, and biochemical production. Geared to practicing engineers faced with designing increasingly more sophisticated control systems in response to present-day economic and regulatory pressures, Plantwide Process Control focuses on the engineering portion of a plant automation improvement project. It features a full control design information package (Control Requirements Definition or CRD), and guides readers through all steps of the automation process—from the initial concept to design, simulation, testing, implementation, and operation. This unique and practical resource:

• Integrates continuous, batch, and discrete control techniques.
• Shows how to use the methodology with any automation project—existing or new, simple or complex, large or small.
• Relates recent ISO and ISA standards to the discipline of control engineering.
• Illustrates the methodology with a pulp-and-paper mill case study.
• Incorporates numerous other examples, from single-loop controllers to multivariable controllers.

This text introduces the principles of maintainability, from the point of view of engineering, mathematics and management, placing the topic in the systems life cycle. This has been achieved by introducing concepts, measures and methodologies for the maintainability prediction and assessment and finally the tools for trade-off between maintainability and other system related attributes are given. A large number of numerical examples are given together with approximately ten case studies related to world-renown systems with the aim of demonstrating the application and importance of maintainability issues in design and operation.

February 27 - March 1, 1997, the conference Optimal Control: The ory, Algorithms, and Applications took place at the University of Florida, hosted by the Center for Applied Optimization. The conference brought together researchers from universities, industry, and government laborato ries in the United States, Germany, Italy, France, Canada, and Sweden. There were forty-five invited talks, including seven talks by students. The conference was sponsored by the National Science Foundation and endorsed by the SIAM Activity Group on Control and Systems Theory, the Mathe matical Programming Society, the International Federation for Information Processing (IFIP), and the International Association for Mathematics and Computers in Simulation (IMACS). Since its inception in the 1940s and 1950s, Optimal Control has been closely connected to industrial applications, starting with aerospace. The program for the Gainesville conference, which reflected the rich cross-disci plinary flavor of the field, included aerospace applications as well as both novel and emerging applications to superconductors, diffractive optics, non linear optics, structural analysis, bioreactors, corrosion detection, acoustic flow, process design in chemical engineering, hydroelectric power plants, sterilization of canned foods, robotics, and thermoelastic plates and shells. The three days of the conference were organized around the three confer ence themes, theory, algorithms, and applications. This book is a collection of the papers presented at the Gainesville conference. We would like to take this opportunity to thank the sponsors and participants of the conference, the authors, the referees, and the publisher for making this volume possible."

"Risks in Technological Systems" is an interdisciplinary university textbook and a book for the educated reader on the risks of today 's society. In order to understand and analyze risks associated with the engineering systems on which modern society relies, other concerns have to be addressed, besides technical aspects. In contrast to many academic textbooks dealing with technological risks, this book has a unique interdisciplinary character that presents technological risks in their own context.

Twenty-four scientists have come together to present their views on risks in technological systems. Their scientific disciplines cover not only engineering, economics and medicine, but also history, psychology, literature and philosophy. Taken together these contributions provide a broad, but accurate, interdisciplinary introduction to a field of increasing global interest, as well as rich opportunities to achieve in-depth knowledge of the subject.

Clearly illustrates how established techniques can be easily understood and used with a sample size that is smaller than normally envisioned. Provides solutions to complex industrial problems by demonstrating how to define the problem and evaluate it statistically with the aim of accelerating product design testing that requires fewer samples and offers more information with less test effort. Along with examples, it contains detailed additional material presented in tabular form for both easy reference and cross-reference.

The UN designated the decade 2005-2015 as the International Decade for Action - Water for Life. The move was initiated at the third World Water Forum in Kyoto, 2003, and it could prove the most significant and effective outcome of the triennial series of World Water For a yet. Its major aims are: (1) to promote efforts to fulfil recent international commitments, especially in the Millennium Goals, (2) to advance towards a truly integrated, int- national approach to sustainable water management, and (3) to put special emphasis on the role of women in these efforts. Even so, it faces tremendous and, as I write, increasing obstacles. The intense season of hurricanes and tropical storms in 2008 illustrated yet again not only the power of nature, but also the vulnerability of the poorer nations, like Haiti and Jamaica. New Orleans and Texas fared better, not because of the efforts of the International Decade for Natural Disasters (1990-2000) to increase preparedness, but more because the USA had learnt from its own experiences in Hurricane Katrina. The biggest obstacle of all is the burgeoning world population. It took off last century, but it is predicted to reach unimaginable heights this century: at least 10 billion by 2050, maybe 20 billion by 2100. Governments are powerless to halt it, even the Chinese. Achieving water security globally against this backdrop will be a Herculean task.

Adaptive Internal Model Control is a methodology for the design and analysis of adaptive internal model control schemes with provable guarantees of stability and robustness. Written in a self-contained tutorial fashion, this research monograph successfully brings the latest theoretical advances in the design of robust adaptive systems to the realm of industrial applications. It provides a theoretical basis for analytically justifying some of the reported industrial successes of existing adaptive internal model control schemes, and enables the reader to synthesise adaptive versions of their own favourite robust internal model control scheme by combining it with a robust adaptive law. The net result is that earlier empirical IMC designs can now be systematically robustified or replaced altogether by new designs with assured guarantees of stability and robustness.