The primary objective of the book is to provide advanced undergraduate or frrst-year graduate engineering students with a self-contained presentation of the principles fundamental to the analysis, design and implementation of computer controlled systems. The material is also suitable for self-study by practicing engineers and is intended to follow a first course in either linear systems analysis or control systerns. A secondary objective of the book is to provide engineering and/or computer science audiences with the material for a junior/senior-level course in modern systems analysis. Chapters 2, 3, 4, and 5 have been designed with this purposein rnind. The emphasis in such a course is to develop the rnathernatical tools and methods suitable for the analysis and design of real-time systems such as digital filters. Thus, engineers and/or computer scientists who know how to program computers can understand the mathematics relevant to the issue of what it is they are programrning. This is especially important for those who may work in engineering and scientific environments where, for instance, programrning difference equations for real-time applications is becorning increasingly common. A background in linear algebra should be an adequate prerequisite for the systems analysis course. Chapter 1 of the book presents a brief introduction to computer controlled systems. It describes the general issues and terminology relevant to the analysis, design, and implementation of such systems.

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.

The book provides background information about technical solutions, processes and methodology to develop future automated mobility solutions. Beginning from the legal requirements as the minimum tolerable risk level of the society, the book provides state-of-the-art risk-management methodologies. The system engineering approach based on todays engineering best practices enhanced by principles derived from cybernetics. The approach derived from the typical behaviour of a human driver in public road traffic to a cybernetical based system engineering approach. Beyond the system engineering approach, a common behaviour model for the operational domain will show aspects how to extend the system engineering model with principles of cybernetics. The role and the human factors of road traffic participants and drivers of motor vehicles are identified and several viewpoints for different observers show how such mixed traffic scenarios could be assessed and optimised. The influence of the changing mobility demands of the society and the resulting changes to the origination of producer, owner, driver and supplier show aspects for future liability and risk share option for new supply chains. Examples from various industries provide some well-proven engineering principles how to adapt those for the future mobility for the benefit of the users. The aim of the book is to raise awareness that the safety provided by a product, a means of transport or a system up to an entire traffic system depends on the capabilities of the various actors. In addition to the driver and passengers, there are also other road users, maintenance personnel and service providers, who must have certain abilities to act safely in traffic. These are also the capabilities of the organisation, not only the organisation that develops or brings the product to market, but also the organisation that is responsible for the operation and the whole lifecycle of the products. The book is for people who want to get involved in the mobility of the future. People, that have ideas to become a player who want to help shape the future mobility of society and who want to bring responsible solutions for users into the market.

Since the emerging discipline of engineering enterprise systems extends traditional systems engineering to develop webs of systems and systems-of-systems, the engineering management and management science communities need new approaches for analyzing and managing risk in engineering enterprise systems. Advanced Risk Analysis in Engineering Enterprise Systems presents innovative methods to address these needs. With a focus on engineering management, the book explains how to represent, model, and measure risk in large-scale, complex systems that are engineered to function in enterprise-wide environments. Along with an analytical framework and computational model, the authors introduce new protocols: the risk co-relationship (RCR) index and the functional dependency network analysis (FDNA) approach. These protocols capture dependency risks and risk co-relationships that may exist in an enterprise. Moving on to extreme and rare event risks, the text discusses how uncertainties in system behavior are intensified in highly networked, globally connected environments. It also describes how the risk of extreme latencies in delivering time-critical data, applications, or services can have catastrophic consequences and explains how to avoid these events. With more and more communication, transportation, and financial systems connected across domains and interfaced with an infinite number of users, information repositories, applications, and services, there has never been a greater need for analyzing risk in engineering enterprise systems. This book gives you advanced methods for tackling risk problems at the enterprise level.

Modern Industrial Statistics The new edition of the prime reference on the tools of statistics used in industry and services, integrating theoretical, practical, and computer-based approaches Modern Industrial Statistics is a leading reference and guide to the statistics tools widely used in industry and services. Designed to help professionals and students easily access relevant theoretical and practical information in a single volume, this standard resource employs a computer-intensive approach to industrial statistics and provides numerous examples and procedures in the popular R language and for MINITAB and JMP statistical analysis software. Divided into two parts, the text covers the principles of statistical thinking and analysis, bootstrapping, predictive analytics, Bayesian inference, time series analysis, acceptance sampling, statistical process control, design and analysis of experiments, simulation and computer experiments, and reliability and survival analysis. Part A, on computer age statistical analysis, can be used in general courses on analytics and statistics. Part B is focused on industrial statistics applications. The fully revised third edition covers the latest techniques in R, MINITAB and JMP, and features brand-new coverage of time series analysis, predictive analytics and Bayesian inference. New and expanded simulation activities, examples, and case studies--drawn from the electronics, metal work, pharmaceutical, and financial industries--are complemented by additional computer and modeling methods. Helping readers develop skills for modeling data and designing experiments, this comprehensive volume: Explains the use of computer-based methods such as bootstrapping and data visualization Covers nonstandard techniques and applications of industrial statistical process control (SPC) charts Contains numerous problems, exercises, and data sets representing real-life case studies of statistical work in various business and industry settings Includes access to a companion website that contains an introduction to R, sample R code, csv files of all data sets, JMP add-ins, and downloadable appendices Provides an author-created R package, mistat, that includes all data sets and statistical analysis applications used in the book Part of the acclaimed Statistics in Practice series, Modern Industrial Statistics with Applications in R, MINITAB, and JMP, Third Edition, is the perfect textbook for advanced undergraduate and postgraduate courses in the areas of industrial statistics, quality and reliability engineering, and an important reference for industrial statisticians, researchers, and practitioners in related fields. The mistat R-package is available from the R CRAN repository.

A one-of-a-kind presentation of the major achievements in statistical profile monitoring methods

Statistical profile monitoring is an area of statistical quality control that is growing in significance for researchers and practitioners, specifically because of its range of applicability across various service and manufacturing settings. Comprised of contributions from renowned academicians and practitioners in the field, "Statistical Analysis of Profile Monitoring" presents the latest state-of-the-art research on the use of control charts to monitor process and product quality profiles. The book presents comprehensive coverage of profile monitoring definitions, techniques, models, and application examples, particularly in various areas of engineering and statistics.

The book begins with an introduction to the concept of profile monitoring and its applications in practice. Subsequent chapters explore the fundamental concepts, methods, and issues related to statistical profile monitoring, with topics of coverage including: Simple and multiple linear profilesBinary response profilesParametric and nonparametric nonlinear profilesMultivariate linear profiles monitoringStatistical process control for geometric specificationsCorrelation and autocorrelation in profilesNonparametric profile monitoring

Throughout the book, more than two dozen real-world case studies highlight the discussed topics along with innovative examples and applications of profile monitoring. "Statistical Analysis of Profile Monitoring" is an excellent book for courses on statistical quality control at the graduate level. It also serves as a valuable reference for quality engineers, researchers and anyone who works in monitoring and improving statistical processes.

This book comprehensively outlines what a holistic and effective Root Cause Analysis (RCA) system looks like. From the designing of the support infrastructure to the measuring of effectiveness on the bottom-line, this book provides the blueprint for making it happen. While traditionally RCA is viewed as a reactive tool, the authors will show how it can be applied proactively to prevent failures from occurring in the first place. RCA is a key element of any successful Reliability Engineering initiative. Such initiatives are comprised of equipment, process and human reliability foundations. Human reliability is critical to the success of a true RCA approach. This book explores the anatomy of a failure (undesirable outcome) as well as a potential failure (high risks). Virtually all failures are triggered by errors of omission or commission by human beings. The methodologies described in this book are applicable to any industry because the focus is on the human being's ability to think through why things go wrong, not on the industry or the nature of the failure. This book correlates reliability to safety as well as human performance improvement efforts. The author has provided a healthy balance between theory and practical application, wrapping up with case studies demonstrating bottom-line results. Features Outlines in detail every aspect of an effective RCA 'system' Displays appreciation for the role of understanding the physics of a failure as well as the human and system's contribution Demonstrates the role of RCA in a comprehensive Asset Performance Management (APM) system Explores the correlation between Reliability Engineering and Safety Integrates the concepts of Human Performance Improvement, Learning Teams, and Human Error Reduction approaches into RCA

- includes MATLABr fundamentals, matrices, arrays, general graphics and specialized plots in quality assurance problems, script files, ordinary and partial differential equations - gives calculation of six sigma, total quality management, time series forecasting, reliability, process improvement, metrology, quality control and assurance, measurement and testing techniques - provides tools for graphical presentation, basic and special statistics and testing, ordinary and partial differential solvers, and fitting tools - includes comprehensive command information in tables Many books are available on MATLABr programming for engineers in general or in some specific area, but none in the highly topical field of quality assurance (QA). MATLABr in quality assurance sciences fills this gap as a compact guide for students, engineers, and scientists in this field. It concentrates on MATLABr fundamentals with examples of application to a wide range of current problems from general, nano and bio-technology, and statistical control, to medicine and industrial management. Examples cover both the school and advanced level; comprising calculations of total quality management, six sigma, time series, process improvement, metrology, quality control, human factors in quality assurance, measurement and testing techniques, quality project and function management, and customer satisfaction. The book covers key topics, including: the basics of software with examples; graphics and representations; numerical computation, scripts and functions for QA calculations; ODE and PDEPE solvers applied to QA problems; curve fitting and time series tool interfaces in calculations of quality; and statistics calculations applied to quality testing.

Everything you need to design, implement, and manage a successful QFD program The QFD Handbook is a total how-to guide for companies planning to initiate a QFD program as well as those that already have one in place. Over the course of 23 contributed chapters, organized according to subject area, this book tutors managers and engineers in basic and advanced QFD principles and practices. Among more advanced topics covered are Taguchi methods, FMEA, TRIZ, and Business Process Reengineering. In addition to traditional application areas, you will find in-depth discussions of QFD in ISO 9000, QS 9000, environmental life cycle, service design, robust design, and software design. On the disk Designed to function in conjunction with the book or as a stand-alone tool for everyday use, the QFD/Pathway software helps QFD teams to develop, deploy, and manage a complete QFD program. This user-friendly, interactive software tool provides valuable assistance at each step of the QFD process, helping members define customer needs, establish goals, translate goals into specific actions, overcome common roadblocks, and more. The QFD Handbook is an indispensable resource for executives, managers, engineers, and R&D professionals who want their companies to survive and thrive in today’s supercompetitive industrial marketplace.

Over the years, companies have developed independent systems for managing process safety, environment, health, safety, and quality. Many aspects of these management systems are similar. Integrating EHS management systems can yield economies and improved system effectiveness. This book explains how integration reduces cost of delivery through a reduction in the number of management program steps and avoidance of redundancy; how it results in more effective programs, since the best practices can be combined into a single process; and how this integration brings a faster, and more cost effective response to new demands.

Reflecting more than 30 years of teaching experience in the field, this guide provides engineers with an introduction to statistics and its applicability to engineering. Examples cover a wide range of engineering applications, including both chemical engineering and semiconductors. Among the topics featured are: quality assurance and statistics, continuous variables, hypothesis testing, comparative experiments, acceptance sampling, the analysis of variance, Taguchi and Orthogonal arrays. Tables, references and an index round out this work.

Covers basic principles and proactive and pragmatic quality function deployment (QFD) methods. Explains how to arrange groups in an industrial organization into design and development teams. Describes how to implement QFD to effectively produce quality products in a fashion that meets customers' needs. This book includes aspects of modern planning techniques, technological forecasting methods and value engineering.

This textbook presents the principal methods of stress analysis for the design of frame structures, beginning with a description of the basic criteria for probabilistic safety verification used in modern codes. The Force Method and the Displacement Method are dealt with, together with their applications to more common structural situations. A special chapter is dedicated to the second order analysis required for slender structures and for the elaboration of instability problems. In turn, a thorough set of numerical examples rounds out the text. Given its scope, the book offers an ideal learning resource for students of Civil and Building Engineering and Architecture, and a valuable reference guide for practicing structural design professionals.

Covers experiment planning, execution, analysis, and reporting This single-source resource guides readers in planning and conducting credible experiments for engineering, science, industrial processes, agriculture, and business. The text takes experimenters all the way through conducting a high-impact experiment, from initial conception, through execution of the experiment, to a defensible final report. It prepares the reader to anticipate the choices faced during each stage. Filled with real-world examples from engineering science and industry, Planning and Executing Credible Experiments: A Guidebook for Engineering, Science, Industrial Processes, Agriculture, and Business offers chapters that challenge experimenters at each stage of planning and execution and emphasizes uncertainty analysis as a design tool in addition to its role for reporting results. Tested over decades at Stanford University and internationally, the text employs two powerful, free, open-source software tools: GOSSET to optimize experiment design, and R for statistical computing and graphics. A website accompanies the text, providing additional resources and software downloads. A comprehensive guide to experiment planning, execution, and analysis Leads from initial conception, through the experiment's launch, to final report Prepares the reader to anticipate the choices faced throughout an experiment Hones the motivating question Employs principles and techniques from Design of Experiments (DoE) Selects experiment designs to obtain the most information from fewer experimental runs Offers chapters that propose questions that an experimenter will need to ask and answer during each stage of planning and execution Demonstrates how uncertainty analysis guides and strengthens each stage Includes examples from real-life industrial experiments Accompanied by a website hosting open-source software Planning and Executing Credible Experiments is an excellent resource for graduates and senior undergraduates--as well as professionals--across a wide variety of engineering disciplines.

The classic introduction to engineering optimization theory and practice--now expanded and updated

Engineering optimization helps engineers zero in on the most effective, efficient solutions to problems. This text provides a practical, real-world understanding of engineering optimization. Rather than belaboring underlying proofs and mathematical derivations, it emphasizes optimization methodology, focusing on techniques and stratagems relevant to engineering applications in design, operations, and analysis. It surveys diverse optimization methods, ranging from those applicable to the minimization of a single-variable function to those most suitable for large-scale, nonlinear constrained problems. New material covered includes the duality theory, interior point methods for solving LP problems, the generalized Lagrange multiplier method and generalization of convex functions, and goal programming for solving multi-objective optimization problems. A practical, hands-on reference and text, Engineering Optimization, Second Edition covers:
* Practical issues, such as model formulation, implementation, starting point generation, and more
* Current, state-of-the-art optimization software
* Three engineering case studies plus numerous examples from chemical, industrial, and mechanical engineering
* Both classical methods and new techniques, such as successive quadratic programming, interior point methods, and goal programming
Excellent for self-study and as a reference for engineering professionals, this Second Edition is also ideal for senior and graduate courses on engineering optimization, including television and online instruction, as well as for in-plant training.

Human Factors in the Chemical and Process Industries: Making it Work in Practice is a comprehensive overview of human factors within this sector, focusing on the practical application. It has been written by acknowledged industry experts from the Keil Centre, which is a leading practice of chartered ergonomics and human factors specialists, chartered safety specialists, registered occupational psychologists, and registered clinical psychologists The book was inspired by the international human factors training course run by the Keil Centre with the IChemE(http://www.icheme.org/human-factors), which has reached four continents across the world. The book is written for those who want a comprehensive overview of the subject, focusing on the practical application of human factors. It has been written for safety professionals, engineers and operational disciplines within industry, and those aspiring to these disciplines, who either deal with human factors issues or any aspect of the 'human element' in their core role. The book explains what 'human factors' is about and how human factors issues are best managed from a practical perspective. It will help readers develop a greater understanding of the area and how to establish more effective solutions for human factors related issues.

A comprehensive presentation of control theory for the SPC community

Quality control has become a major concern in today’s competitive industrial environment, and industrial engineers are constantly seeking to make process adjustments that will optimize production efficiency and improve product quality. Statistical Process Adjustment for Quality Control fills the need for a comprehensive presentation of control theory at the elementary level, focusing on statistical methods used in process adjustment (Engineering Process Control Methods or EPC) and their relation to the classical methods of process monitoring, particularly those using SPC control charts. The author presents the severe effects of autocorrelated data on control chart performance and advocates the use of active adjustment methods for improving the quality of products and processes. He uses a detailed explanation of Deming’s funnel experiment to illustrate the need for process adjustment when there are process dynamics, and presents an in-depth description of ARIMA models and Transfer Function models from a statistical point of view. He offers several adjustment strategies, including Minimum Variance Controllers, PID controllers, EWMA controllers, deadband policies, and constrained variance controllers. The book also offers integration strategies for SPC and EPC methods, discusses multivariate ARMAX models used for multivariate adjustment, and provides readers with a brief introduction to frequency domain and state-space methods.

Statistical Process Adjustment for Quality Control is a timely resource for students, industrial engineers, and applied statisticians in both academic and industrial settings. Unique features include:

• A strong focus on quality control of products and processes
• Broad coverage of SPC, adjustments, and time series under one cover
• Abundant examples using both real process data and simulations
• Detailed explanations on how to use SAS and MATLAB on an accompanying ftp site
• Coverage of spreadsheet simulation and optimization models in Microsoft Excel
• Numerous chapter problems and detailed bibliography of relevant literature for further reading

With the growing use of feedback controls, "hard" nonlinearities have become ubiquitous in engineering practice despite their rare treatment in academic texts. This book introduces a unified adaptive inverse approach for the control of systems with unknown nonlinearities and settles long-standing engineering problems posed by imperfections of actuators and sensors.

Focusing on dead-zone, backlash, and hysteresis, the authors show how real-time computations can counteract the effects of these nonlinearities. In many applications their approach avoids the need for costly and specialized hardware.

This easy-to-use, self-contained presentation of the entirely new adaptive inverse design is geared towards practicing engineers, researchers, and graduate students.

Adaptive Control of Systems with Actuator and Sensor Nonlinearities features:

• Systematic treatment for actuator and sensor nonlinearities.
• Examples of dead-zone, backlash, and hysteresis models and their inverses.
• Broad coverage that ranges from satellite antennas and piezo-positioners to industrial automation and consumer electronics.
• Step-by-step instructions for adaptive inverse design and implementation.
• Unified continuous- and discrete-time presentation.
• A concise review of model reference adaptive control theory.
• Extensive illustrations of system performance improvement.
• Over ninety figures and design examples.

The engineering objective of high performance control using the tools of optimal control theory, robust control theory, and adaptive control theory is more achiev able now than ever before, and the need has never been greater. Of course, when we use the term high peiformance control we are thinking of achieving this in the real world with all its complexity, uncertainty and variability. Since we do not expect to always achieve our desires, a more complete title for this book could be "Towards High Performance Control." To illustrate our task, consider as an example a disk drive tracking system for a portable computer. The better the controller performance in the presence of eccen tricity uncertainties and external disturbances, such as vibrations when operated in a moving vehicle, the more tracks can be used on the disk and the more memory it has. Many systems today are control system limited and the quest is for high performance in the real world."

Structures that are essential for economy and security such as energy production, transportation and supply, water supply, buildings, are susceptible to failure, because of defects already present in the material, or created at fabrication, or appearing during service. Methods of assesment of the nocivity of these defects are needed, to predict the remaining service life and the eventual emergency of stopping service and repairing, if possible. To reach this objectives, this book presents the last methods derived from the classical linear, non-linear fracture mechanics concepts, including fatigue and notch fracture mechanics. Several examples of structures rehabilitations and repairing are given.

This book gathers the presentation made during the Advanced Research Workshop held in Portoroz (Slovenia) in October 2008, under the auspices of NATO Science for Peace and Security Programme. It is edited by Professor Guy Pluvinage from the University Paul Verlaine Metz (France) and Professor Aleksandar Sedmak from the University of Belgrade, Faculty of Mechanical Engineering. Both have a long and rich experience in analysis of theoretical and practical cases in safety and reliability of structures. Other contributors are all known as experts in the areas of fatigue, facture and reliability of structures."

For sophomore or junior-level courses in industrial engineering. Divided into two major areas of study - work systems, and work methods, measurement, and management - this guidebook provides up-to-date, quantitative coverage of work systems and how work is analyzed and designed. Thorough, broad-based coverage addresses nearly all of the traditional topics of industrial engineering that relate to work systems and work science. The author's quantitative approach summarizes many aspects of work systems, operations analysis, and work measurement using mathematical equations and quantitative examples.

Engineering Decisions for Life Quality: How Safe is Safe Enough? provides a foundation and a theoretical basis for managing risk to an acceptable level under the real-world constraint of limited resources. The focus is not on risks as such, but on what can be done to maximize the positive outcomes of risk in terms of improvements to the quality of life.

The principal focus of Engineering Decisions for Life Quality: How Safe is Safe Enough? is on the development of guidance for establishing rational standards of practice. Standards should meet the requirement of utilizing resources to achieve the maximum net overall benefit to society within society's capacity to commit such resources.

The ideas discussed within this book will be of interest to engineers; advanced undergraduate and graduate students; public health officials; and risk specialists.

This book provides the latest research advances in the field of system reliability assurance and engineering. It contains reference material for applications of reliability in system engineering, offering a theoretical sound background with adequate numerical illustrations. Included are concepts pertaining to reliability analysis, assurance techniques and methodologies, tools, and practical applications of system reliability modeling and allocation. The collection discusses various soft computing techniques like artificial intelligence and particle swarm optimization approach for reliability assessment. Importance of differentiating between the optimal release time and testing stop time of the software has been explicitly discussed and presented in the book. Features: Creates understanding of the costs associated with complex systems Covers reliability measurement of engineering systems Incorporates an efficient effort-based expenditure policy incorporating cost and reliability criteria Provides information for optimal testing stop and release time of software system Presents software performance and security layout Addresses reliability prediction and its maintenance through advanced analytics techniques Overall, System Reliability Management: Solutions and Techniques is a collaborative and interdisciplinary approach for better communication of problems and solutions to increase the performance of the system for better utilization and resource management.

This volume presents a rigorous account of statistical forecasting efforts that led to the successful resolution of the Johns-Manville asbestos litigation. This case, taking 12 years to reach settlement, is expected to generate nearly 500,000 claims at a total nominal value of over $34 billion. The forecasting task, to project the number, timing, and nature of claims for asbestos-related injuries from a set of exposed persons of unknown size, is a general problem: the models in this volume can be adapted to forecast industry-wide asbestos liability. More generally, because the models are not overly dependent on the U.S. legal system and the role of asbestos as a dangerous/defective product, this volume will be of interest in other product liability cases, as well as similar forecasting situations for a range of insurable or compensable events. The volume stresses the iterative nature of model building and the uncertainty generated by lack of complete knowledge of the injury process. This uncertainty is balanced against the Court's need for a definitive settlement, and the volume addresses how these opposing principles can be reconciled. The volume is written for a broad audience of actuaries, biostatisticians, demographers, economists, epidemiologists, environmental health scientists, financial analysts, industrial-risk analysts, occumpational health analysts, product liability analysts, and statisticians. The modest prerequisites include basic concepts of statistics, calculus, and matrix algebra. Care is taken that readers without specialized knowledge in these areas can understand the rationale for specific applications of advanced methods. As a consequence, this volume will be an indispensable reference for all whose work involves these topics. Eric Stallard, A.S.A., M.A.A.A., is Research Professor and Associate Director of the Center for Demographic Studies at Duke University. He is a Member of the American Academy of Actuaries and an Associate of the Society of Actuaries. He serves on the American Academy of Actuaries Committees on Long Term Care and Social Insurance. He also serves on the society of Actuaries' Long Term Care Experience Committee. His research interests include modelling and forecasting for medical demography and health actuarial practice. He was the 1996 winner of the National Institute on Aging's James A. Shannon Director's Award. Kenneth G. Manton, Ph.D., is Research Professor, Research Director, and Director of the Center for Demographic Studies at Duke University and Medical Research Professor at Duke University Medical Center's Department of Community and Family Medicine. Dr. Manton is also a Senior Fellow of the Duke University Medical Center's Center for the Study of Aging and Human Development. His research interests include mathematical models of human aging, mortality, and chronic disease. He was the 1990 recipient of the Mindel C. Sheps Award in Mathematical Demography presented by the Population Association of America; and in 1991 he received the Allied-Signal Inc. Achievement Award in Aging administred by the Johns Hopkins Center on Aging. Joel E. Cohen, Ph.D., Dr. P.H., is Professor of Populations, and Head of the Laboratory of Populations, Rockefeller University. He also is Professor of Populations at Columbia University. His research interests include the demography, ecology, epidemiology, and social organization of human and non-human populations, and related mathematical concepts. In 1981, he was elected Fellow of the MacArthur and Guggenheim Foundations. He was the 1992 recipient of the Mindel C. Sheps Award in Mathematical Demography presented by the Population Association of America; and in 1994, he received the Distinguished Statistical Ecologist Award at the Sixth International Congress of Ecology.

Gets professionals quickly on-line with all the crucial design concepts and skills they need to dramatically improve the maintainability of their products or systems

Maintainability is a practical, step-by-step guide to implementing a comprehensive maintainability program within your organization's design and development function. From program scheduling, organizational interfacing, cost estimating, and supplier activities, to maintainability prediction, task analysis, formal design review, and maintainability tests and demonstrations, it describes all the planning and organizational aspects of maintainability for projects under development and

• Schools readers in state-of-the-art maintainability design techniques
• Demonstrates methods for quantitatively measuring maintainability at every stage of the development process
• Shows how to increase effectiveness while reducing life-cycle costs of already existing systems or products
• Features numerous case studies, sample applications, and practice exercises
• Functions equally well as a professional reference and a classroom text

Independent cost analysis studies indicate that an inordinately large percentage of the overall life-cycle cost of most systems/products is currently taken up by maintenance and support. In fact, for many large-scale systems, maintenance and support have been shown to account for as much as 60% to 75% of overall life-cycle costs. At a time of fierce global competition, long-term cost effectiveness is a major competitive advantage that manufacturers simply cannot afford to underestimate. Clearly then, to remain competitive in today's international marketplace, companies must institute programs for reducing system maintenance and support costs— comprehensive programs that are an integral part of the design and development process from its earliest conceptual stages.

This book shows you how to implement such a program within your organization's design and development function. From program scheduling, organizational interfacing, cost estimating, and supplier activities, to maintainability prediction, task analysis, formal design review, and maintainability tests and demonstrations, it describes all the planning and organizational aspects of maintainability for projects under development while schooling you in the use of the full range of proven design techniques—including methods for quantitatively measuring maintainability at every stage of the development process. The authors also clearly explain how the principles and practices outlined in Maintainability can be applied to the evaluation of systems/products now in use both to increase their effectiveness and reduce long-term costs.

While theoretical aspects of maintainability are discussed, the authors' main purpose in writing this book is to help get professionals quickly on-line with the essential maintainability concepts and skills. Hence, in addition to clarity of presentation and a rational hierarchical format, Maintainability features many case studies and sample applications that help to clarify the points covered, and numerous practice exercises that help engineers to test their mastery of the concepts and techniques covered.

Maintainability is an invaluable professional tool for engineers from all disciplines who are involved with the design, testing, prototyping, manufacturing, and maintenance of products and systems. It also serves as a superior course book for graduate-level programs in those disciplines.