The rich palette of topics set out in this book provides a sufficiently broad overview of the developments in the field of quality control. By providing detailed information on various aspects of quality control, this book can serve as a basis for starting interdisciplinary cooperation, which has increasingly become an integral part of scientific and applied research.

Quality control is a constant priority in electrical, mechanical, aeronautical, and nuclear engineering – as well as in the vast domain of electronics, from home appliances to computers and telecommunications. Quality Control Applications provides guidance and valuable insight into quality control policies; their methods, their implementation, constant observation and associated technical audits. What has previously been a mostly mathematical topic is translated here for engineers concerned with the practical implementation of quality control. Once the fundamentals of quality control are established, Quality Control Applications goes on to develop this knowledge and explain how to apply it in the most effective way. Techniques are described and supported using relevant, real-life, case studies to provide detail and clarity for those without a mathematical background. Among the many practical examples, two case studies dramatize the importance of quality assurance: A shot-by-shot analysis of the errors made in the Fukushima Daiichi nuclear disaster; and the engineering failure with new technology due to the absence of quality control in an alternative energy project. This clear and comprehensive approach makes Quality Control Applications an essential reference for those studying engineering as well industry professionals involved in quality control across product and system design.

Rapid advance have been made in the last decade in the quality control procedures and techniques, most of the existing books try to cover specific techniques with all of their details. The aim of this book is to demonstrate quality control processes in a variety of areas, ranging from pharmaceutical and medical fields to construction engineering and data quality. A wide range of techniques and procedures have been covered.

Quality control is changing along with the manufacturing environment. A series of revolutionary changes will occur in management contents, methods, capabilities, and real-time effectiveness and efficiency of management. As an essential factor in intelligent manufacturing, quality control systems require real and comprehensive innovation. Focused on new trends and developments in quality control from a worldwide perspective, this book presents the latest information on novel approaches in quality control. Its thirteen chapters cover three topics: intelligent manufacturing, robust design, and control charts.

Presenting a practitioner's guide to capabilities and best practices of quality control systems using the R programming language, this volume emphasizes accessibility and ease-of-use through detailed explanations of R code as well as standard statistical methodologies. In the interest of reaching the widest possible audience of quality-control professionals and statisticians, examples throughout are structured to simplify complex equations and data structures, and to demonstrate their applications to quality control processes, such as ISO standards. The volume balances its treatment of key aspects of quality control, statistics, and programming in R, making the text accessible to beginners and expert quality control professionals alike. Several appendices serve as useful references for ISO standards and common tasks performed while applying quality control with R.

Quality assurance and accreditation in analytical chemistry laboratories is an important issue on the national and international scale. The book presents currently used methods to assure the quality of analytical results and it describes accreditation procedures for the mutual recognition of these results. The book describes in detail the accreditation systems in 13 European countries and the present situation in the United States of America. The editor also places high value on accreditation and certification practice and on the relevant legislation in Europe. The appendix lists invaluable information on important European accreditation organizations.

Machine Vision systems combine image processing with industrial automation. One of the primary areas of application of Machine Vision in the Industry is in the area of Quality Control. Machine vision provides fast, economic and reliable inspection that improves quality as well as business productivity. Building machine vision applications is a challenging task as each application is unique, with its own requirements and desired outcome. A Guide to Machine Vision in Quality Control follows a practitioner’s approach to learning machine vision. The book provides guidance on how to build machine vision systems for quality inspections. Practical applications from the Industry have been discussed to provide a good understanding of usage of machine vision for quality control. Real-world case studies have been used to explain the process of building machine vision solutions. The book offers comprehensive coverage of the essential topics, that includes: Introduction to Machine Vision Fundamentals of Digital Images Discussion of various machine vision system components Digital image processing related to quality control Overview of automation The book can be used by students and academics, as well as by industry professionals, to understand the fundamentals of machine vision. Updates to the on-going technological innovations have been provided with a discussion on emerging trends in machine vision and smart factories of the future. Sheila Anand is a PhD graduate and Professor at Rajalakshmi Engineering College, Chennai, India. She has over three decades of experience in teaching, consultancy and research. She has worked in the software industry and has extensive experience in development of software applications and in systems audit of financial, manufacturing and trading organizations. She guides Ph.D. aspirants and many of her research scholars have since been awarded their doctoral degree. She has published many papers in national and international journals and is a reviewer for several journals of repute. L Priya is a PhD graduate working as Associate Professor and Head, Department of Information Technology at Rajalakshmi Engineering College, Chennai, India. She has nearly two decades of teaching experience and good exposure to consultancy and research. She has delivered many invited talks, presented papers and won several paper awards in International Conferences. She has published several papers in International journals and is a reviewer for SCI indexed journals. Her areas of interest include Machine Vision, Wireless Communication and Machine Learning.