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Author: Rabindra Nath Das Publisher: ISBN: 9781306865937 Category : Languages : en Pages : 333
Book Description
Although widely used in science and technology for experimental data generating, modeling, and optimization, the response surface methodology (RSM) has many limitations. Showing how robust response surface methodology (RRSM) can overcome these limitations, Robust Response Surfaces, Regression, and Positive Data Analyses presents RRS designs, along with the relevant regression and positive data analysis techniques. It explains how to use RRSM in experimental designs and regression analysis. The book addresses problems of RRS designs, such as rotatability, slope-rotatability, weak rotatability, and optimality. It describes methods for estimating model parameters as well as positive data analysis techniques. The author illustrates the concepts and methods with real examples of lifetime responses, resistivity, replicated measures, and more. The range of topics and applications gives the book broad appeal both to theoreticians and practicing professionals. The book helps quality engineers, scientists in any area, medical practitioners, demographers, economists, and statisticians understand the theory and applications of RRSM. It can also be used in a second course on the design of experiments.
Author: Rabindra Nath Das Publisher: ISBN: 9781306865937 Category : Languages : en Pages : 333
Book Description
Although widely used in science and technology for experimental data generating, modeling, and optimization, the response surface methodology (RSM) has many limitations. Showing how robust response surface methodology (RRSM) can overcome these limitations, Robust Response Surfaces, Regression, and Positive Data Analyses presents RRS designs, along with the relevant regression and positive data analysis techniques. It explains how to use RRSM in experimental designs and regression analysis. The book addresses problems of RRS designs, such as rotatability, slope-rotatability, weak rotatability, and optimality. It describes methods for estimating model parameters as well as positive data analysis techniques. The author illustrates the concepts and methods with real examples of lifetime responses, resistivity, replicated measures, and more. The range of topics and applications gives the book broad appeal both to theoreticians and practicing professionals. The book helps quality engineers, scientists in any area, medical practitioners, demographers, economists, and statisticians understand the theory and applications of RRSM. It can also be used in a second course on the design of experiments.
Author: Rabindra Nath Das Publisher: CRC Press ISBN: 1466506806 Category : Mathematics Languages : en Pages : 333
Book Description
Although widely used in science and technology for experimental data generating, modeling, and optimization, the response surface methodology (RSM) has many limitations. Showing how robust response surface methodology (RRSM) can overcome these limitations, Robust Response Surfaces, Regression, and Positive Data Analyses presents RRS designs, along
Author: Andre I. Khuri Publisher: Routledge ISBN: 1351418696 Category : Mathematics Languages : en Pages : 307
Book Description
Response Surfaces: Designs and Analyses; Second Edition presents techniques for designing experiments that yield adequate and reliable measurements of one or several responses of interest, fitting and testing the suitability of empirical models used for acquiring information from the experiments, and for utilizing the experimental results to make decisions concerning the system under investigation. This edition contains chapters on response surface models with block effects and on Taguchi's robust parameter design, additional details on transformation of response variable, more material on modified ridge analysis, and new design criteria, including rotatability for multiresponse experiments. It also presents an innovative technique for displaying correlation among several response. Numerical examples throughout the book plus exercises--with worked solutions to selected problems--complement the text.
Author: Young J. Chiang Publisher: SAE International ISBN: 1468607693 Category : Computers Languages : en Pages : 398
Book Description
Failure modes and effects analysis (FMEA); Reliability; Product Development; Design Process; Test Procedures "Explore Product Design and Testing for Automotive Engineering: Volume II, an essential guide reshaping vehicle manufacturing with unprecedented reliability. As part of SAE International’s DOE for Product Reliability Growth series, this practical resource introduces cutting-edge methodologies crucial for predicting and improving product reliability in an era of automotive electrification. The book navigates statistical tolerance design, showcasing how variability in part fabrication and assembly can enhance reliability and sustainability. Key topics include: - Statistical tolerance design's impact on manufacturing and material selection, focusing on non-normal distributions' effects on product assembly and cost. Methods like maximum likelihood estimators and Monte Carlo simulations are used for assembly strategy synthesis. - Reliability DOEs using log-location-scale distributions to estimate lifetimes of non-normally distributed components, especially in accelerated life testing. It covers transformations optimizing parts and system designs under the lognormal distribution. - Weibull distribution (DOE-W) for characterizing lifetimes affected by various failure modes, detailing parameter assessment methods and real-world applications. The book also introduces reliability design of experiments based on the exponential distribution (DOE-E). - Importance of predicting lifecycles and enhancing reliability through qualitative and stepwise accelerated life tests. Integration of physics of failure with statistical methods like Weibull statistics and lognormal approximation enhances analysis credibility. - Inferential mechanisms such as the Arrhenius and Eyring models in predicting automotive component lifecycles, refining product life prediction based on reliability DOEs. Whether you're an engineer, researcher, or automotive professional, this book equips you to navigate reliability engineering confidently. Revolutionize your approach to product design and testing with Product Design and Testing for Automotive Engineering, your definitive companion in shaping the future of automotive reliability." (ISBN 9781468607703 ISBN 9781468607697 ISBN 9781468607727 DOI 10.4271/9781468607697)
Author: Andr I. Khuri Publisher: World Scientific ISBN: 9812774734 Category : Mathematics Languages : en Pages : 474
Book Description
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."
Author: Raymond H. Myers Publisher: John Wiley & Sons ISBN: 1118210476 Category : Science Languages : en Pages : 596
Book Description
Praise for the Second Edition: "This book [is for] anyone who would like a good, solid understanding of response surface methodology. The book is easy to read, easy to understand, and very applicable. The examples are excellent and facilitate learning of the concepts and methods." —Journal of Quality Technology Complete with updates that capture the important advances in the field of experimental design, Response Surface Methodology, Third Edition successfully provides a basic foundation for understanding and implementing response surface methodology (RSM) in modern applications. The book continues to outline the essential statistical experimental design fundamentals, regression modeling techniques, and elementary optimization methods that are needed to fit a response surface model from experimental data. With its wealth of new examples and use of the most up-to-date software packages, this book serves as a complete and modern introduction to RSM and its uses across scientific and industrial research. This new edition maintains its accessible approach to RSM, with coverage of classical and modern response surface designs. Numerous new developments in RSM are also treated in full, including optimal designs for RSM, robust design, methods for design evaluation, and experiments with restrictions on randomization as well as the expanded integration of these concepts into computer software. Additional features of the Third Edition include: Inclusion of split-plot designs in discussion of two-level factorial designs, two-level fractional factorial designs, steepest ascent, and second-order models A new section on the Hoke design for second-order response surfaces New material on experiments with computer models Updated optimization techniques useful in RSM, including multiple responses Thorough treatment of presented examples and experiments using JMP 7, Design-Expert Version 7, and SAS software packages Revised and new exercises at the end of each chapter An extensive references section, directing the reader to the most current RSM research Assuming only a fundamental background in statistical models and matrix algebra, Response Surface Methodology, Third Edition is an ideal book for statistics, engineering, and physical sciences courses at the upper-undergraduate and graduate levels. It is also a valuable reference for applied statisticians and practicing engineers.
Author: Raymond H. Myers Publisher: Wiley ISBN: 9781118916018 Category : Mathematics Languages : en Pages : 856
Book Description
Praise for the Third Edition: “This new third edition has been substantially rewritten and updated with new topics and material, new examples and exercises, and to more fully illustrate modern applications of RSM.” - Zentralblatt Math Featuring a substantial revision, the Fourth Edition of Response Surface Methodology: Process and Product Optimization Using Designed Experiments presents updated coverage on the underlying theory and applications of response surface methodology (RSM). Providing the assumptions and conditions necessary to successfully apply RSM in modern applications, the new edition covers classical and modern response surface designs in order to present a clear connection between the designs and analyses in RSM. With multiple revised sections with new topics and expanded coverage, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition includes: Many updates on topics such as optimal designs, optimization techniques, robust parameter design, methods for design evaluation, computer-generated designs, multiple response optimization, and non-normal responses Additional coverage on topics such as experiments with computer models, definitive screening designs, and data measured with error Expanded integration of examples and experiments, which present up-to-date software applications, such as JMP®, SAS, and Design-Expert®, throughout An extensive references section to help readers stay up-to-date with leading research in the field of RSM An ideal textbook for upper-undergraduate and graduate-level courses in statistics, engineering, and chemical/physical sciences, Response Surface Methodology: Process and Product Optimization Using Designed Experiments, Fourth Edition is also a useful reference for applied statisticians and engineers in disciplines such as quality, process, and chemistry.
Author: Lawrence Publisher: CRC Press ISBN: 9780824781293 Category : Mathematics Languages : en Pages : 320
Book Description
Combining theory, methodology, and applications in a unified survey, this important reference/text presents the most recent results in robust regression analysis, including properties of robust regression techniques, computational issues, forecasting, and robust ridge regression. It provides useful case studies so that students and engineers can apply these techniques to forecasting, quantitative business analysis, econometrics, marketing, statistics, and demand modeling. Robust Regression: Analysis and Applications characterizes robust estimators in terms of how much they weight each observation ... discusses generalized properties of L[subscript p]-estimators ... includes an algorithm for identifying outliers using least absolute value criterion in regression modeling ... reviews redescending M-estimators ... studies L[subscript 1] linear regression ... proposes the best linear unbiased estimators for fixed parameters and random errors in the mixed linear model ... summarizes known properties of L[subscript 1] estimators for time series analysis ... examines ordinary least squares, latent root regression, and a robust regression weighting scheme ... and evaluates results from five different robust ridge regression estimators. Containing 120 tables and diagrams plus numerous bibliographic citations, Robust Regression: Analysis and Applications is the leading reference for applied statisticians, operations researchers, econometricians, marketing forecasters, business administration and management scientists, and industrial engineers as well as a text for graduate statistics or economics courses. Book jacket.
Author: Anthony Atkinson Publisher: Springer Science & Business Media ISBN: 1461211603 Category : Mathematics Languages : en Pages : 342
Book Description
Graphs are used to understand the relationship between a regression model and the data to which it is fitted. The authors develop new, highly informative graphs for the analysis of regression data and for the detection of model inadequacies. As well as illustrating new procedures, the authors develop the theory of the models used, particularly for generalized linear models. The book provides statisticians and scientists with a new set of tools for data analysis. Software to produce the plots is available on the authors website.
Author: Rabindra Nath Das
Author: Rabindra Nath Das
Author: Rabindra Nath Das
Author: Andre I. Khuri
Author: Young J. Chiang
Author: Andr I. Khuri
Author: Raymond H. Myers
Author: André I. Khuri
Author: Raymond H. Myers
Author: Lawrence
Author: Anthony Atkinson