How to Run Mixture Experiments for Product Quality

How to Run Mixture Experiments for Product Quality
Author: John A. Cornell
Publisher: ASQ Quality Press
Total Pages: 108
Release: 1990
Genre: Business & Economics
ISBN:

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This set of helpful analytical tools is written for practitioners who perform and analyze mixture experiments. It is a concise treatment of techniques for designing, modeling, and interpreting data from these experiments.Contents:An Overview The Simplex-Lattice Designs and Associated Polynomial Models Multiple Constraints of the Component Proportions The Analysis of Mixture Data The Inclusion of Process Variables in Mixture Experiments

Experiments with Mixtures

Experiments with Mixtures
Author: John A. Cornell
Publisher: John Wiley & Sons
Total Pages: 682
Release: 2011-09-20
Genre: Mathematics
ISBN: 111815049X

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The most comprehensive, single-volume guide to conductingexperiments with mixtures "If one is involved, or heavily interested, in experiments onmixtures of ingredients, one must obtain this book. It is, as wasthe first edition, the definitive work." -Short Book Reviews (Publication of the International StatisticalInstitute) "The text contains many examples with worked solutions and with itsextensive coverage of the subject matter will prove invaluable tothose in the industrial and educational sectors whose work involvesthe design and analysis of mixture experiments." -Journal of the Royal Statistical Society "The author has done a great job in presenting the vitalinformation on experiments with mixtures in a lucid and readablestyle. . . . A very informative, interesting, and useful book on animportant statistical topic." -Zentralblatt fur Mathematik und Ihre Grenzgebiete Experiments with Mixtures shows researchers and students how todesign and set up mixture experiments, then analyze the data anddraw inferences from the results. Virtually every technique thathas appeared in the literature of mixtures can be found here, andcomputing formulas for each method are provided with completelyworked examples. Almost all of the numerical examples are takenfrom real experiments. Coverage begins with Scheffe latticedesigns, introducing the use of independent variables, and endswith the most current methods. New material includes: * Multiple response cases * Residuals and least-squares estimates * Categories of components: Mixtures of mixtures * Fixed as well as variable values for the major componentproportions * Leverage and the Hat Matrix * Fitting a slack-variable model * Estimating components of variances in a mixed model using ANOVAtable entries * Clarification of blocking mates and choice of mates * Optimizing several responses simultaneously * Biplots for multiple responses

A Primer on Experiments with Mixtures

A Primer on Experiments with Mixtures
Author: John A. Cornell
Publisher: John Wiley & Sons
Total Pages: 376
Release: 2011-09-26
Genre: Mathematics
ISBN: 0470907428

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The concise yet authoritative presentation of key techniques for basic mixtures experiments Inspired by the author's bestselling advanced book on the topic, A Primer on Experiments with Mixtures provides an introductory presentation of the key principles behind experimenting with mixtures. Outlining useful techniques through an applied approach with examples from real research situations, the book supplies a comprehensive discussion of how to design and set up basic mixture experiments, then analyze the data and draw inferences from results. Drawing from his extensive experience teaching the topic at various levels, the author presents the mixture experiments in an easy-to-follow manner that is void of unnecessary formulas and theory. Succinct presentations explore key methods and techniques for carrying out basic mixture experiments, including: Designs and models for exploring the entire simplex factor space, with coverage of simplex-lattice and simplex-centroid designs, canonical polynomials, the plotting of individual residuals, and axial designs Multiple constraints on the component proportions in the form of lower and/or upper bounds, introducing L-Pseudocomponents, multicomponent constraints, and multiple lattice designs for major and minor component classifications Techniques for analyzing mixture data such as model reduction and screening components, as well as additional topics such as measuring the leverage of certain design points Models containing ratios of the components, Cox's mixture polynomials, and the fitting of a slack variable model A review of least squares and the analysis of variance for fitting data Each chapter concludes with a summary and appendices with details on the technical aspects of the material. Throughout the book, exercise sets with selected answers allow readers to test their comprehension of the material, and References and Recommended Reading sections outline further resources for study of the presented topics. A Primer on Experiments with Mixtures is an excellent book for one-semester courses on mixture designs and can also serve as a supplement for design of experiments courses at the upper-undergraduate and graduate levels. It is also a suitable reference for practitioners and researchers who have an interest in experiments with mixtures and would like to learn more about the related mixture designs and models.

Statistical Methods for Quality Improvement

Statistical Methods for Quality Improvement
Author: Thomas P. Ryan
Publisher: John Wiley & Sons
Total Pages: 578
Release: 2011-09-20
Genre: Technology & Engineering
ISBN: 1118058100

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Praise for the Second Edition "As a comprehensive statistics reference book for quality improvement, it certainly is one of the best books available." —Technometrics This new edition continues to provide the most current, proven statistical methods for quality control and quality improvement The use of quantitative methods offers numerous benefits in the fields of industry and business, both through identifying existing trouble spots and alerting management and technical personnel to potential problems. Statistical Methods for Quality Improvement, Third Edition guides readers through a broad range of tools and techniques that make it possible to quickly identify and resolve both current and potential trouble spots within almost any manufacturing or nonmanufacturing process. The book provides detailed coverage of the application of control charts, while also exploring critical topics such as regression, design of experiments, and Taguchi methods. In this new edition, the author continues to explain how to combine the many statistical methods explored in the book in order to optimize quality control and improvement. The book has been thoroughly revised and updated to reflect the latest research and practices in statistical methods and quality control, and new features include: Updated coverage of control charts, with newly added tools The latest research on the monitoring of linear profiles and other types of profiles Sections on generalized likelihood ratio charts and the effects of parameter estimation on the properties of CUSUM and EWMA procedures New discussions on design of experiments that include conditional effects and fraction of design space plots New material on Lean Six Sigma and Six Sigma programs and training Incorporating the latest software applications, the author has added coverage on how to use Minitab software to obtain probability limits for attribute charts. new exercises have been added throughout the book, allowing readers to put the latest statistical methods into practice. Updated references are also provided, shedding light on the current literature and providing resources for further study of the topic. Statistical Methods for Quality Improvement, Third Edition is an excellent book for courses on quality control and design of experiments at the upper-undergraduate and graduate levels. the book also serves as a valuable reference for practicing statisticians, engineers, and physical scientists interested in statistical quality improvement.

Response Surface Methodology and Related Topics

Response Surface Methodology and Related Topics
Author: Andr‚ I. Khuri
Publisher: World Scientific
Total Pages: 474
Release: 2006
Genre: Mathematics
ISBN: 9812774734

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This is the first edited volume on response surface methodology (RSM). It contains 17 chapters written by leading experts in the field and covers a wide variety of topics ranging from areas in classical RSM to more recent modeling approaches within the framework of RSM, including the use of generalized linear models. Topics covering particular aspects of robust parameter design, response surface optimization, mixture experiments, and a variety of new graphical approaches in RSM are also included. The main purpose of this volume is to provide an overview of the key ideas that have shaped RSM, and to bring attention to recent research directions and developments in RSM, which can have many useful applications in a variety of fields. The volume will be very helpful to researchers as well as practitioners interested in RSM''s theory and potential applications. It will be particularly useful to individuals who have used RSM methods in the past, but have not kept up with its recent developments, both in theory and applications. Sample Chapter(s). Chapter 1: Two-Level Factorial and Fractional Factorial Designs in Blocks of Size Two. Part 2 (560 KB). Contents: Two-Level Factorial and Fractional Factorial Designs in Blocks of Size Two. Part 2 (Y J Yang & N R Draper); Response Surface Experiments on Processes with High Variation (S G Gilmour & L A Trinca); Random Run Order, Randomization and Inadvertent Split-Plots in Response Surface Experiments (J Ganju & J M Lucas); Statistical Inference for Response Surface Optima (D K J Lin & J J Peterson); A Search Method for the Exploration of New Regions in Robust Parameter Design (G Mer-Quesada & E del Castillo); Response Surface Approaches to Robust Parameter Design (T J Robinson & S S Wulff); Response Surface Methods and Their Application in the Treatment of Cancer with Drug Combinations: Some Reflections (K S Dawson et al.); Generalized Linear Models and Response Transformation (A C Atkinson); GLM Designs: The Dependence on Unknown Parameters Dilemma (A I Khuri & S Mukhopadhyay); Design for a Trinomial Response to Dose (S K Fan & K Chaloner); Evaluating the Performance of Non-Standard Designs: The San Cristobal Design (L M Haines); 50 Years of Mixture Experiment Research: 1955OCo2004 (G F Piepel); Graphical Methods for Comparing Response Surface Designs for Experiments with Mixture Components (H B Goldfarb & D C Montgomery); Graphical Methods for Assessing the Prediction Capability of Response Surface Designs (J J Borkowski); Using Fraction of Design Space Plots for Informative Comparisons between Designs (C M Anderson-Cook & A Ozol-Godfrey); Concepts of Slope-Rotatability for Second Order Response Surface Designs (S H Park); Design of Experiments for Estimating Differences between Responses and Slopes of the Response (S Huda). Readership: Researchers in academia and industry interested in response surface methodology and its applications; engineers interested in improving quality and productivity in industry."

Statistical Methods for Testing, Development, and Manufacturing

Statistical Methods for Testing, Development, and Manufacturing
Author: Forrest W. Breyfogle, III
Publisher: John Wiley & Sons
Total Pages: 556
Release: 1992-04-16
Genre: Business & Economics
ISBN: 9780471540359

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Clearly illustrates how established techniques can be easily understood and used with a sample size that is smaller than normally envisioned. Provides solutions to complex industrial problems by demonstrating how to define the problem and evaluate it statistically with the aim of accelerating product design testing that requires fewer samples and offers more information with less test effort. Along with examples, it contains detailed additional material presented in tabular form for both easy reference and cross-reference.

Practical Design of Experiments (DOE)

Practical Design of Experiments (DOE)
Author: Mark Allen Durivage
Publisher: Quality Press
Total Pages: 225
Release: 2016-02-25
Genre: Business & Economics
ISBN: 0873899245

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This book was written to aid quality technicians and engineers. It is a result of 30 years of quality-related work experience. To that end, the intent of this book is to provide the quality professional working in virtually any industry a quick, convenient, and comprehensive guide to properly conducting design of experiments (DOE) for the purpose of process optimization. This is a practical introduction to the basics of DOE, intended for people who have never been exposed to design of experiments, been intimidated in their attempts to learn about DOE, or have not appreciated the potential of this family of tools in their process improvement and optimization efforts. In addition, this book is a useful reference when preparing for and taking many of the ASQ quality certification examinations, including the Certified Quality Technician (CQT), Certified Six Sigma Green Belt (CSSGB), Certified Quality Engineer (CQE), Certified Six Sigma Black Belt (CSSBB), and Certified Reliability Engineer (CRE).

Formulation Simplified

Formulation Simplified
Author: Mark J. Anderson
Publisher: Taylor & Francis
Total Pages: 190
Release: 2018-04-17
Genre: Business & Economics
ISBN: 1351677527

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Many chemists – especially those most brilliant in their field – fail to appreciate the power of planned experimentation. They dislike the mathematical aspects of statistical analysis. In addition, these otherwise very capable chemists also dismissed predictive models based only on empirical data. Ironically, in the hands of subject matter experts like these elite chemists, the statistical methods of mixture design and analysis provide the means for rapidly converging on optimal compositions. What differentiates Formulation Simplified from the standard statistical texts on mixture design is that the authors make the topic relatively easy and fun to read. They provide a whole new collection of insighful original studies that illustrate the essentials of mixture design and analysis. Solid industrial examples are offered as problems at the end of many chapters for those who are serious about trying new tools on their own. Statistical software to do the computations can be freely accessed via a web site developed in support of this book.

Implementing Six Sigma

Implementing Six Sigma
Author: Forrest W. Breyfogle, III
Publisher: John Wiley & Sons
Total Pages: 1232
Release: 2003-04-07
Genre: Technology & Engineering
ISBN: 0471265721

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Includes new and expanded coverage of Six Sigma infrastructure building and benchmarking. Provides plans, checklists, metrics, and pitfalls.

An Introduction to Design of Experiments

An Introduction to Design of Experiments
Author: Larry B. Barrentine
Publisher: Quality Press
Total Pages: 122
Release: 2001-09-25
Genre: Business & Economics
ISBN: 0873891341

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This book is intended for people who have either been intimidated in their attempts to learn about Design of Experiments (DOE) or who have not appreciated the potential of that family of tools in their process improvement efforts. This introduction to DOE showcases the power and utility of this statistical tool while teaching the audience how to plan and analyze an experiment. It is also an attempt to dispel the conception that DOE is reserved only for those with advanced mathematics training. It will be demonstrated that DOE is primarily a logic tool that can be easily grasped and applied, requiring only basic math skills. The book's intent is to introduce the basics and persuade the reader of the power of this tool. The material covered will still be sufficient to support a high proportion of the experiments one may wish to perform. Contents:Introduction, Experiments with Two Factors, The Analytical Procedures, The Eight Steps for Analysis of Effects, Review of the Experimental Procedures, The Spreadsheet Approach, Experiments with Three Factors, Variation Analysis, Analysis with Unreplicated Experiments, Screening Design, Other Types of Design, Problems and Questions, Review of the Basics in Managing DOE, What Inhibits Applications of DOE?