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This book provides a common sense computer-oriented, determinstic manufacturing approach, which employs statistics but does not require a background in this area, theoretical mathematics or computer science to understand and apply. In a clear, easy-to-read style, this reference text highlights critical parameters that have a major impact upon process quality and identifies sensors for parameter monitoring; discusses appropriate applications of deterministic techniques to many manifacturing situations ranging from simple to complex; includes chapter summaries, helpful illustrations and numerous citations to ehnance comprehension and facilitate further research. Written from the perspective of a practioner who 'knows how to make parts'; presenting practical solutions to manufacturing problems it is essential reading for industrial, quality control, electrical and electronics, mechancial, manufacturing and systems engineers/managers and undergraduate and graduate-level students in the above areas.
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.
This book presents an organized approach to quality management, control, and improvement. Because quality problems usually are the outcome of uncontrolled or excessive variability, statistical tools and other analytical methods play an important role in solving these problems. However, these techniques need to be implemented within a management structure that will ensure success. This text focuses on both the management structure and the statistical and analytical tools. It organizes and presents this material according to many years of teaching, research, and professional practice across a wide range of business and industrial settings.
Using actual examples of software process improvement from the private sector and government, this work demonstrates how quality systems, measurement techniques and performance evaluations work. It presents a methodology for analyzing an ongoing software development process and establishing a rational plan for process improvement.
Introduction -- Hardware Integration -- Software Integration -- Integration of Statistical Methods -- Facility Integration -- Summary -- References -- CHAPTER 11: Factory of the Future -- Introduction -- Manufacturing Cells -- Flexible Manufacturing Systems -- Material Handling -- Fault Tolerance -- References -- Index
This book covers the foundations of modern methods of quality control and improvement that are used in the manufacturing and service industries. Quality is key to surviving tough competition. Consequently, business needs technically competent people who are well-versed in statistical quality control and improvement. This book should serve the needs of students in business and management and students in engineering, technology, and other related disciplines. Professionals will find this book to be a valuable reference in the field.
Standards, Quality Control and Measurement Sciences in 3D Printing and Additive Manufacturing addresses the critical elements of the standards and measurement sciences in 3D printing to help readers design and create safe, reliable products of high quality. With 3D printing revolutionizing the process of manufacturing in a wide range of products, the book takes key features into account, such as design and fabrication and the current state and future potentials and opportunities in the field. In addition, the book provides an in-depth analysis on the importance of standards and measurement sciences. With self-test exercises at the end of each chapter, readers can improve their ability to take up challenges and become proficient in a number of topics related to 3D printing, including software usage, materials specification and benchmarking. - Helps the reader understand the quality framework tailored for 3D printing processes - Explains data format and process control in 3D printing - Provides an overview of different materials and characterization methods - Covers benchmarking and metrology for 3D printing
Revised and expanded, this Second Edition continues to explore the modern practice of statistical quality control, providing comprehensive coverage of the subject from basic principles to state-of-the-art concepts and applications. The objective is to give the reader a thorough grounding in the principles of statistical quality control and a basis for applying those principles in a wide variety of both product and nonproduct situations. Divided into four parts, it contains numerous changes, including a more detailed discussion of the basic SPC problem-solving tools and two new case studies, expanded treatment on variable control charts with new examples, a chapter devoted entirely to cumulative-sum control charts and exponentially-weighted, moving-average control charts, and a new section on process improvement with designed experiments.
Ellis Ott taught generations of quality practitioners to be explorers of the truth through the collection and graphical portrayal of data. From a simple plea to "plot the data" to devising a graphical analytical tool called the analysis of means (ANOM), Ott demonstrated that process knowledge is to be gained by seeking the information contained within the data.In this newest version of Ott's classic text, the authors have strived to continue down the path that he created for others to follow. Additions to this revised edition include: the use of dot plots as an alternative to histograms; digidot plots; adding events to charts; emphasis on the role that acceptance control charts play in controlling risks and the computation of average run length (ARL); a new chapter devoted to process capability, process performance, and process improvement, including the use of confidence intervals for process capability metrics; narrow-limit gauging as another means of assessing the capability of a process; Six Sigma methodology; design resolution; scatter plot matrices as applied to datasets of higher dimensions; and a new chapter on measurement studies.