Testing of materials and manufactured items is a key element in the process from standard specification through control and verification during manufacture to trade in actual products. In particular, the validity, reliability and economic aspects of testing are of importance. This process is becoming more urgent with the development of the European market and other developments in international trade. Considerable progress is being made in setting up cooperative agreements and networks both bilaterally and multilaterally between countries, covering reference materials, and calibration, accreditation and quality assurance of laboratories, equipment and staff. This book contains invited contributions from many of the individuals and organizations most closely involved in these international developments. Also included are papers and case studies from all parts of the world discussing particular aspects of test quality of construction, materials and structures. The volume should be useful for those responsible for managing and carrying out testing in commercial, industrial and research laboratories, and also for anyone with an interest in international harmonization of technical stand

This book is concerned with Intelligent Control methods and applications. The field of intelligent control has been expanded very much during the recent years and a solid body of theoretical and practical results are now available. These results have been obtained through the synergetic fusion of concepts and techniques from a variety of fields such as automatic control, systems science, computer science, neurophysiology and operational research. Intelligent control systems have to perform anthropomorphic tasks fully autonomously or interactively with the human under known or unknown and uncertain environmental conditions. Therefore the basic components of any intelligent control system include cognition, perception, learning, sensing, planning, numeric and symbolic processing, fault detection/repair, reaction, and control action. These components must be linked in a systematic, synergetic and efficient way. Predecessors of intelligent control are adaptive control, self-organizing control, and learning control which are well documented in the literature. Typical application examples of intelligent controls are intelligent robotic systems, intelligent manufacturing systems, intelligent medical systems, and intelligent space teleoperators. Intelligent controllers must employ both quantitative and qualitative information and must be able to cope with severe temporal and spatial variations, in addition to the fundamental task of achieving the desired transient and steady-state performance. Of course the level of intelligence required in each particular application is a matter of discussion between the designers and users. The current literature on intelligent control is increasing, but the information is still available in a sparse and disorganized way.

Formerly titled Quality Control, the field's most accessible introduction to quality has been renamed and revamped to focus on quantitative aspects of quality improvement. New chapters on Lean Enterprise, Six Sigma, Experimental Design, and Taguchi's Quality Engineering have been added, and this new Ninth Edition adds comprehensive coverage of fundamental statistical quality improvement concepts. A practical state-of-the-art approach is stressed throughout, and sufficient theory is presented to ensure that students develop a solid understanding of basic quality principles. To improve accessibility, probability and statistical techniques are presented through simpler math or developed via tables and charts. As with previous editions, this text is written to serve a widely diverse audience of students, including the growing number of "math shy" individuals who must play key roles in quality improvement.

Model based control has emerged as an important way to improve plant efficiency in the process industries, while meeting processing and operating policy constraints. The reader of Methods of Model Based Process Control will find state of the art reports on model based control technology presented by the world's leading scientists and experts from industry. All the important issues that a model based control system has to address are covered in depth, ranging from dynamic simulation and control-relevant identification to information integration. Specific emerging topics are also covered, such as robust control and nonlinear model predictive control. In addition to critical reviews of recent advances, the reader will find new ideas, industrial applications and views of future needs and challenges. Audience: A reference for graduate-level courses and a comprehensive guide for researchers and industrial control engineers in their exploration of the latest trends in the area.

This richly illustrated book describes statistical extreme value theory for the quantification of natural hazards, such as strong winds, floods and rainfall, and discusses an interdisciplinary approach to allow the theoretical methods to be applied. The approach consists of a number of steps: data selection and correction, non-stationary theory (to account for trends due to climate change), and selecting appropriate estimation techniques based on both decision-theoretic features (e.g., Bayesian theory), empirical robustness and a valid treatment of uncertainties. It also examines and critically reviews alternative approaches based on stochastic and dynamic numerical models, as well as recently emerging data analysis issues and presents large-scale, multidisciplinary, state-of-the-art case studies. Intended for all those with a basic knowledge of statistical methods interested in the quantification of natural hazards, the book is also a valuable resource for engineers conducting risk analyses in collaboration with scientists from other fields (such as hydrologists, meteorologists, climatologists).

This book is written primarily for engineers who want to use statistical designs for quality engineering, and for statisticians who want to know the wide range of applications of experimental design in the manufacturing industry. Significantly, Robust Design and Analysis for Quality Engineering addresses the following techniques: Taguchi's quality engineering approaches, concepts of robustness in experimental designs, response surface design and its applications, Pareto-type ANOVA for analysis of parameter design, and strategies of quality improvement efforts through robust design and analysis. Through a series of real case studies, these important techniques are made readily accessible to all readers. This is also the key text for senior undergraduate and postgraduate students studying engineering and experimental design.

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.

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

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.

- 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 book covers the application of psychological principles and techniques to situations and problems of aviation. It offers an overview of the role psychology plays in aviation, system design, selection and training of pilots, characteristics of pilots, safety, and passenger behavior. It covers concepts of psychological research and data analysis and shows how these tools are used in the development of new psychological knowledge. The new edition offers material on physiological effects on pilot performance, a new chapter on aviation physiology, more material on fatigue, safety culture, mental health and safety, as well as practical examples and exercises after each chapter.

Table of Contents

Introduction. Research Methods and Statistics. Aviation Physiology. Abilities and Personality Traits. Personnel Selection. Training. Human Factors and the Design of Aviation Systems. Stress and Human Reactions. Culture, Organizations and Leadership. Aeronautical Decision-Making. Aviation Safety. Concluding Remarks.

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.

Risk-based, Management-led, Audit-driven, Safety Management Systems, explains what a safety management system (SMS) is, and how it reduces risk in order to prevent accidental losses in an organization. It advocates the integration of safety and health into the day-to-day management of the enterprise as a value, rather than an add-on, and emphasizes that the safety movement must be initiated, led and maintained by management at all levels.

The concepts of safety authority, responsibility and accountability are described as the key ingredients to safety system success. Safety system audits are expounded in simple terms, and leading safety performance indicators are suggested as the most important measurements, in preference to lagging indicators. McKinnon highlights the importance of the identification and control of risk as a key basis for a SMS, with examples of a simple risk matrix and daily task risk assessment, as well as a simplified method of assessing, analyzing, and controlling risks.

The book refers to international Guidelines on SMS, as well as the proposed International Organization for Standardization (ISO) 45001, which could soon become the international safety benchmark for organizations worldwide. Using clear, approachable examples, the chapters give a complete overview of an SMS and its components. Confirming to most of the safety management system Guidelines published by leading world authorities, this volume will allow organizations to structure their own world-class SMS.

Table of Contents

Chapter 1: Introduction

Chapter 2: Accident Causation

Chapter 3: Safety Management Systems and Guidelines

Chapter 4: Risk-based Safety Management Systems

Chapter 5: Management-led Safety Management Systems

Chapter 6: Audit-Driven Safety Management Systems

Chapter 7: Safety Leadership and Organization – Part 1

Chapter 8: Safety Leadership and Organization Elements – Part 2

Chapter 9: Electrical, Mechanical, and Personal Safeguarding – Part 1

Chapter 9: Electrical, Mechanical, and Personal Safeguarding – Part 2

Chapter 11: Emergency Preparedness, Fire Prevention and Protection

Chapter 12: Accident and Near Miss Incident Recording and Investigation

Chapter 13: Workplace Environment Conditions

Chapter 14: Safety Management System Implementation Strategy

Chapter 15: Measuring Performance

Chapter 16: Case Study

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.

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.

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.