John Stufken

Bio: John Stufken is an academic researcher from Arizona State University. The author has contributed to research in topics: Optimal design & Orthogonal array. The author has an hindex of 23, co-authored 80 publications receiving 1930 citations. Previous affiliations of John Stufken include University of Georgia & Iowa State University.

Taguchi Methods: A Hands-On Approach

Abstract: American industry is now realizing that applying Dr. Genichi Taguchi's now-famous quality-engineering techniques can improve their products and produce substantial savings in cost and time. Until now, it has been difficult to find a clear explanation of the key terms and principles of Taguchi's methods. In Peace's book, industrial engineers will discover a practical, readable guide that demonstrates Taguchi techniques step-by-step. Unique coverage of the different types of quality characteristics ensure that readers will understand how to measure and choose options when applying this technology. The book focuses on one of Taguchi's core techniques, "Design of Experiments", which helps engineers test their products and processes and design robust products at the lowest possible cost. Case studies illustrate Taguchi methods at work in a varietyof situations.

Handbook of Design and Analysis of Experiments

Abstract: General Principles History and Overview of Design and Analysis of Experiments Klaus Hinkelmann Introduction to Linear Models Linda M. Haines Designs for Linear Models Blocking with Independent Responses John P. Morgan Crossover Designs Mausumi Bose and Aloke Dey Response Surface Experiments and Designs Andre I. Khuri and Siuli Mukhopadhyay Design for Linear Regression Models with Correlated Errors Holger Dette, Andrey Pepelyshev, and Anatoly Zhigljavsky Designs Accommodating Multiple Factor Regular Fractional Factorial Designs Robert Mee and Angela Dean Multistratum Fractional Factorial Designs Derek Bingham Nonregular Factorial and Supersaturated Designs Hongquan Xu Structures Defined by Factors R.A. Bailey Algebraic Method in Experimental Design Hugo Maruri-Aguilar and Henry P. Wynn Optimal Design for Nonlinear and Spatial Models Optimal Design for Nonlinear and Spatial Models: Introduction and Historical Overview Douglas P. Wiens Designs for Generalized Linear Models Anthony C. Atkinson and David C. Woods Designs for Selected Nonlinear Models Stefanie Biedermann and Min Yang Optimal Design for Spatial Models Zhengyuan Zhu and Evangelos Evangelou Computer Experiments Design of Computer Experiments: Introduction and Background Max Morris and Leslie Moore Latin Hypercubes and Space-Filling Designs C. Devon Lin and Boxin Tang Design for Sensitivity Analysis William Becker and Andrea Saltelli Expected Improvement Designs William I. Notz Cross-Cutting Issues Robustness of Design Douglas P. Wiens Algorithmic Searches for Optimal Designs Abhyuday Mandal, Weng Kee Wong, and Yaming Yu Design for Contemporary Applications Design for Discrete Choice Experiments Heiko Grossmann and Rainer Schwabe Plate Designs in High-Throughput Screening Experiments for Drug Discovery Xianggui Qu (Harvey) and Stanley Young Up-and-Down Designs for Dose-Finding Nancy Flournoy and Assaf P. Oron Optimal Design for Event-Related fMRI Studies Jason Ming-Hung Kao and John Stufken Index

Information-Based Optimal Subdata Selection for Big Data Linear Regression

Abstract: Extraordinary amounts of data are being produced in many branches of science. Proven statistical methods are no longer applicable with extraordinary large datasets due to computational limitations....

Support points of locally optimal designs for nonlinear models with two parameters

Abstract: We propose a new approach for identifying the support points of a locally optimal design when the model is a nonlinear model. In contrast to the commonly used geometric approach, we use an approach based on algebraic tools. Considerations are restricted to models with two parameters, and the general results are applied to often used special cases, including logistic, probit, double exponential and double reciprocal models for binary data, a loglinear Poisson regression model for count data, and the Michaelis-Menten model. The approach, which is also of value for multi-stage experiments, works both with constrained and unconstrained design regions and is relatively easy to implement.

The Design and Analysis of Experiments

Abstract: THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

Optimization of fused deposition modeling process parameters: a review of current research and future prospects

Abstract: Fused deposition modeling (FDM) is one of the most popular additive manufacturing technologies for various engineering applications. FDM process has been introduced commercially in early 1990s by Stratasys Inc., USA. The quality of FDM processed parts mainly depends on careful selection of process variables. Thus, identification of the FDM process parameters that significantly affect the quality of FDM processed parts is important. In recent years, researchers have explored a number of ways to improve the mechanical properties and part quality using various experimental design techniques and concepts. This article aims to review the research carried out so far in determining and optimizing the process parameters of the FDM process. Several statistical designs of experiments and optimization techniques used for the determination of optimum process parameters have been examined. The trends for future FDM research in this area are described.

Ionic polymer–metal composites: II. Manufacturing techniques

Abstract: This paper, the second in a series of four review papers to appear in this journal, presents a detailed description of various techniques and experimental procedures in manufacturing ionic polymer–metal composites (IPMCs) that, if fully developed, can be used as effective biomimetic sensors, actuators and artificial muscles as well as fully electroded with embedded electrodes for fuel cells. The performance of IPMCs manufactured by different manufacturing techniques are presented and compared. In particular, a number of issues such as force optimization using the Taguchi design of experiment technique, effects of different cations on electromechanical performance of IPMCs, electrode and particle size and distribution control, manufacturing cost minimization approaches, scaling and three-dimensional (3D) muscle production issues and heterogeneous composites by physical loading techniques are also reviewed and discussed.

Handbook of Functional MRI Data Analysis

Abstract: Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook of Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

Optimization of wire electrical discharge machining (WEDM) process parameters using Taguchi method

Abstract: Wire electrical discharge machining (WEDM) is extensively used in machining of conductive materials when precision is of prime importance. Rough cutting operation in WEDM is treated as a challenging one because improvement of more than one machining performance measures viz. metal removal rate (MRR), surface finish (SF) and cutting width (kerf) are sought to obtain a precision work. Using Taguchi’s parameter design, significant machining parameters affecting the performance measures are identified as discharge current, pulse duration, pulse frequency, wire speed, wire tension, and dielectric flow. It has been observed that a combination of factors for optimization of each performance measure is different. In this study, the relationship between control factors and responses like MRR, SF and kerf are established by means of nonlinear regression analysis, resulting in a valid mathematical model. Finally, genetic algorithm, a popular evolutionary approach, is employed to optimize the wire electrical discharge machining process with multiple objectives. The study demonstrates that the WEDM process parameters can be adjusted to achieve better metal removal rate, surface finish and cutting width simultaneously.