Author: Richard K. Burdick Publisher: SIAM ISBN: 9780898718379 Category : Technology & Engineering Languages : en Pages : 219
Book Description
This book provides a protocol for conducting gauge repeatability and reproducibility (R&R) experiments. Such an experiment is required whenever a new test system is developed to monitor a manufacturing process. The protocol presented here is used to determine if the testing system is capable of monitoring the manufacturing process with the desired level of accuracy and precision. This protocol is not currently available in other books or technical reports. In addition to providing a protocol for testing a measurement system, the book presents an up-to-date summary of methods used to construct confidence intervals in normal-based random and mixed analysis of variance (ANOVA) models. Thus, this comprehensive book will be useful to scientists in all fields of application who wish to construct interval estimates for ANOVA model parameters. It includes approaches that can be applied to any ANOVA model, and because it contains detailed examples of all computations, practitioners will be able to easily apply the methods. The book describes methods for constructing two types of confidence intervals: modified large-sample (MLS) and generalized confidence intervals. Computer codes written in SAS and Excel are provided to perform the computations. Appendices are included for readers who are unfamiliar with confidence intervals or lack a basic understanding of random and mixed ANOVA models.
Author: Mark Allen Durivage Publisher: Quality Press ISBN: 0873899156 Category : Technology & Engineering Languages : en Pages : 170
Book Description
This book a result of 30 years of quality-related work experience was written to aid quality technicians and engineers. It provides the quality professional working in virtually any industry a quick, convenient, and comprehensive guide to properly conducting measurement systems analysis (MSA). The intent of this book is to provide background and examples on the application of gage R&R methodology (test method validation) for variable and attribute data, help for those who work with devices that dont fit the usual approach, and ideas for measurement devices that require innovation to assess their performance under off-line, static conditions. The ultimate objective is to determine how best to improve the control and performance of a process. The reader is assumed to be familiar with basic control charting methodology since assessment of statistical control of the measurement process is important. One may wonder why performing a gage R&R is so important; the simple answers are profit, public health, and safety. Companies that are shipping product that is out of specification can be subjected to expensive litigation, especially in the aviation, pharmaceutical, and medical device industries. This book will be a useful reference when preparing for and taking many of the ASQ quality certification examinations, including the Certified Quality Technician (CQT), Certified Calibration Technician (CCT), Certified Quality Inspector (CQI), Certified Six Sigma Green Belt (CSSGB), Certified Quality Engineer (CQE), Certified Six Sigma Black Belt (CSSBB), and Certified Reliability Engineer (CRE).
Author: Donald J. Wheeler Publisher: SPC Press, Incorporated ISBN: Category : Business & Economics Languages : en Pages : 132
Book Description
The procedures : inadequate measurement units - Consistency and bias - Interpreting measurements - EMP studies : components of measurement error - The relative usefulness of a measurement - EMP case histories : the data for gauge 130 - Two methods for measuring viscosity - The truck spoke data - The data for polymer 62S - The compression test data.
Author: Mario Perez-Wilson Publisher: ISBN: 9781883237523 Category : Languages : en Pages : 424
Book Description
Process Control, the statistical control step of the best-selling methodology for process characterization, optimization and control --the MPCpS Methodology-- offers a step-by-step approach into monitoring and controlling processes. If you need to improve your process, increase the yield, reduce variation, or identify the most influential process parameters, let process-improvement expert Mario Perez-Wilson show you how. This book walks you through a system that integrates the necessary tools to establish a preventive and continuous plan to control critical machine parameters, significant process variables and product characteristics during production. This guarantees a stable, capable and fool-proof process free of defects. Just follow this step-by-step approach at your own pace and teach yourself how to control processes. You will be improving processes right away!
Author: Theodore T. Allen Publisher: Springer Science & Business Media ISBN: 1849960003 Category : Technology & Engineering Languages : en Pages : 573
Book Description
Lean production, has long been regarded as critical to business success in many industries. Over the last ten years, instruction in six sigma has been increasingly linked with learning about the elements of lean production. Introduction to Engineering Statistics and Lean Sigma builds on the success of its first edition (Introduction to Engineering Statistics and Six Sigma) to reflect the growing importance of the "lean sigma" hybrid. As well as providing detailed definitions and case studies of all six sigma methods, Introduction to Engineering Statistics and Lean Sigma forms one of few sources on the relationship between operations research techniques and lean sigma. Readers will be given the information necessary to determine which sigma methods to apply in which situation, and to predict why and when a particular method may not be effective. Methods covered include: • control charts and advanced control charts, • failure mode and effects analysis, • Taguchi methods, • gauge R&R, and • genetic algorithms. The second edition also greatly expands the discussion of Design For Six Sigma (DFSS), which is critical for many organizations that seek to deliver desirable products that work first time. It incorporates recently emerging formulations of DFSS from industry leaders and offers more introductory material on the design of experiments, and on two level and full factorial experiments, to help improve student intuition-building and retention. The emphasis on lean production, combined with recent methods relating to Design for Six Sigma (DFSS), makes Introduction to Engineering Statistics and Lean Sigma a practical, up-to-date resource for advanced students, educators, and practitioners.
Author: Stephen B. Vardeman Publisher: Springer ISBN: 038779106X Category : Mathematics Languages : en Pages : 447
Book Description
This undergraduate statistical quality assurance textbook clearly shows with real projects, cases and data sets how statistical quality control tools are used in practice. Among the topics covered is a practical evaluation of measurement effectiveness for both continuous and discrete data. Gauge Reproducibility and Repeatability methodology (including confidence intervals for Repeatability, Reproducibility and the Gauge Capability Ratio) is thoroughly developed. Process capability indices and corresponding confidence intervals are also explained. In addition to process monitoring techniques, experimental design and analysis for process improvement are carefully presented. Factorial and Fractional Factorial arrangements of treatments and Response Surface methods are covered. Integrated throughout the book are rich sets of examples and problems that help readers gain a better understanding of where and how to apply statistical quality control tools. These large and realistic problem sets in combination with the streamlined approach of the text and extensive supporting material facilitate reader understanding. Second Edition Improvements Extensive coverage of measurement quality evaluation (in addition to ANOVA Gauge R&R methodologies) New end-of-section exercises and revised-end-of-chapter exercises Two full sets of slides, one with audio to assist student preparation outside-of-class and another appropriate for professors’ lectures Substantial supporting material Supporting Material Seven R programs that support variables and attributes control chart construction and analyses, Gauge R&R methods, analyses of Fractional Factorial studies, Propagation of Error analyses and Response Surface analyses Documentation for the R programs Excel data files associated with the end-of-chapter problem sets, most from real engineering settings
Author: National Academies of Sciences, Engineering, and Medicine Publisher: National Academies Press ISBN: 0309486165 Category : Science Languages : en Pages : 257
Book Description
One of the pathways by which the scientific community confirms the validity of a new scientific discovery is by repeating the research that produced it. When a scientific effort fails to independently confirm the computations or results of a previous study, some fear that it may be a symptom of a lack of rigor in science, while others argue that such an observed inconsistency can be an important precursor to new discovery. Concerns about reproducibility and replicability have been expressed in both scientific and popular media. As these concerns came to light, Congress requested that the National Academies of Sciences, Engineering, and Medicine conduct a study to assess the extent of issues related to reproducibility and replicability and to offer recommendations for improving rigor and transparency in scientific research. Reproducibility and Replicability in Science defines reproducibility and replicability and examines the factors that may lead to non-reproducibility and non-replicability in research. Unlike the typical expectation of reproducibility between two computations, expectations about replicability are more nuanced, and in some cases a lack of replicability can aid the process of scientific discovery. This report provides recommendations to researchers, academic institutions, journals, and funders on steps they can take to improve reproducibility and replicability in science.
Author: Emilio L. Cano Publisher: Springer Science & Business Media ISBN: 1461436524 Category : Mathematics Languages : en Pages : 296
Book Description
Six Sigma has arisen in the last two decades as a breakthrough Quality Management Methodology. With Six Sigma, we are solving problems and improving processes using as a basis one of the most powerful tools of human development: the scientific method. For the analysis of data, Six Sigma requires the use of statistical software, being R an Open Source option that fulfills this requirement. R is a software system that includes a programming language widely used in academic and research departments. Nowadays, it is becoming a real alternative within corporate environments. The aim of this book is to show how R can be used as the software tool in the development of Six Sigma projects. The book includes a gentle introduction to Six Sigma and a variety of examples showing how to use R within real situations. It has been conceived as a self contained piece. Therefore, it is addressed not only to Six Sigma practitioners, but also to professionals trying to initiate themselves in this management methodology. The book may be used as a text book as well.
Author: Peter R. Nelson Publisher: SIAM ISBN: 089871592X Category : Mathematics Languages : en Pages : 252
Book Description
The analysis of means (ANOM) is a graphical procedure used to quantify differences among treatment groups in a variety of experimental design and observational study situations. The ANOM decision chart allows one to easily draw conclusions and interpret results with respect to both statistical and practical significance. It is an excellent choice for multiple comparisons of means, rates, or proportions and can be used with both balanced and unbalanced data. Key advances in ANOM procedures that have appeared only in technical journals during the last 20 years are included in this first comprehensive modern treatment of the ANOM containing all of the needed information for practitioners to understand and apply ANOM. The Analysis of Means: A Graphical Method for Comparing Means, Rates, and Proportions contains examples from a wide variety of fields adapted from real-world applications and data with easy-to-follow, step-by-step instructions. It is front loaded, so potential ANOM users can find solutions to standard problems in the first five chapters. An appendix contains several SAS® examples showing the system's ANOM capabilities and how SAS was used to produce selected ANOM decision charts in the book.Given these features, the lack of any other book on ANOM, and the recent inclusion of ANOM in SAS, this book will be a welcome addition to practitioners' and statisticians' bookshelves, where it will serve both as a primer and reference.Applied statisticians, particularly consulting statisticians, will find that the graphical aspect of ANOM makes it easy to convey results to nonstatisticians. Industrial, process, and quality engineers will find that the ANOM decisions charts offer an ideal interface with management and can be instrumental in selling research conclusions. The ANOM procedures are great for comparing the rates and proportions found in managed health care settings, and for comparing outcomes in multiarm studies done by statistical researchers in medicine.
Author: Donald J. Wheeler Publisher: S P C Press ISBN: 9780945320678 Category : Evaluating Measurement Process Languages : en Pages : 316
Book Description
Techniques for assessing and characterizing physical measurement systems are organized, described, and illustrated using real data. Clear answers are given to the question of how and when imperfect data can be used in practice. This book will enable you to use imperfect data to characterize and improve your operations and processes.64 Examples, 40 Data Tables, 8 Appendicies, 25 Reference Tables, 3 Worksheets
Author: Richard K. Burdick
Author: Mark Allen Durivage
Author: Donald J. Wheeler
Author: Mario Perez-Wilson
Author: Theodore T. Allen
Author: Stephen B. Vardeman
Author: National Academies of Sciences, Engineering, and Medicine
Author: Emilio L. Cano
Author: Peter R. Nelson
Author: Donald J. Wheeler