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Experiments: Planning, Analysis, and Parameter Design Optimization
C. F. Jeff Wu,Michael S. Hamada +1 more
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TLDR
This book discusses Factorial and Fractional Factorial Experiments at Three Levels, Robust Parameter Design for Signal-Response Systems, and other Design and Analysis Techniques for Experiments for Improving Reliability.Abstract:
Basic Principles and Experiments with a Single Factor. Experiments With More Than One Factor. Full Factorial Experiments at Two Levels. Fractional Factorial Experiments at Two Levels. Full Factorial and Fractional Factorial Experiments at Three Levels. Other Design and Analysis Techniques for Experiments at More Than Two Levels. Nonregular Designs: Construction and Properties. Experiments with Complex Aliasing. Response Surface Methodology. Introduction to Robust Parameter Design. Robust Parameter Design for Signal-Response Systems. Experiments for Improving Reliability. Experiments With Nonnormal Data. Appendices. Indexes.read more
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Journal ArticleDOI
The design and analysis of computer experiments
TL;DR: This paper presents a meta-modelling framework for estimating Output from Computer Experiments-Predicting Output from Training Data and Criteria Based Designs for computer Experiments.
Journal ArticleDOI
Recent advances in surrogate-based optimization
TL;DR: The present state of the art of constructing surrogate models and their use in optimization strategies is reviewed and extensive use of pictorial examples are made to give guidance as to each method's strengths and weaknesses.
Journal ArticleDOI
Anisotropic material properties of fused deposition modeling ABS
TL;DR: In this article, the properties of FDM parts fabricated by the FDM 1650 were analyzed using a Design of Experiment (DOE) approach, such as raster orientation, air gap, bead width, color and model temperature.
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Preliminary guidelines for empirical research in software engineering
Barbara Kitchenham,Shari Lawrence Pfleeger,Lesley M. Pickard,Peter W. Jones,D.C. Hoaglin,K. El Emam,J. Rosenberg +6 more
TL;DR: A preliminary set of research guidelines aimed at stimulating discussion among software researchers, intended to assist researchers, reviewers, and meta-analysts in designing, conducting, and evaluating empirical studies.
Response Surface Methodology.
TL;DR: A survey of the various stages in the development of response surface methodology RSM is given in this article, which includes a review of basic experimental designs for fitting linear response surface models, in addition to a description of methods for the determination of optimum operating conditions.