Book Review: Experiments: Planning, Analysis, and Parameter Design Optimization. By C. F. Jeff Wu and Michael Hamada. John Wiley & Sons, Inc., New York, 2000, 630 p., U.S.$89.95 (hb), ISBN…

By T. Jones. 2003

1,116 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Computational Theory and Mathematics, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/5005cf49cc9b345e10264059f790940e24cbeae2

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Citations in the corpus

Classification of Orthogonal Arrays by Integer Programming (2008, background): “Assuming that the hierarchical ordering principle is valid (see Wu and Hamada, 2000, section 3.5), two OA(N, k, s, t) can be compared based on their statistical merits and demerits under model uncertainty using the generalized minimum aberration (GMA) criterion developed by Xu and Wu (2001).”
The generalization of Latin hypercube sampling (2015, result): “This result, combined with the Hierarchical Ordering Principle [13] – which states that main effects and low order interactions are likely to govern most general transformations – causes LHS to reduce variance significantly for many applications.”
Material Characterization of Fused Deposition Modeling (FDM) ABS by Designed Experiments (2001, background): “5 Trouble with contours - Gaps, stress concentration, and (2) direction loading resulting in premature failure.”
Generalized minimum aberration for asymmetrical fractional factorial designs (2001, methodology): “An underlying assumption for minimum aberration and GMA is the hierarchical ordering principle [Wu and Hamada (2000), Section 3.5]: (i) lower order effects are more likely to be important than higher order effects, (ii) effects of the same order are equally likely to be important.”
The Role of Statistical Design of Experiments in Six Sigma: Perspectives of a Practitioner (2002, background): “Case studies have also helped to bring about a deeper appreciation of the need to integrate engineering insights with statistical considerations (41,42).”
Variance-based sensitivity analysis of model outputs using surrogate models (2011, methodology): “This was confirmed by a preliminary investigation using an optimal 219e10V fractional factorial design (Wu and Hamada, 2000) in which the whole set of 19 inputs varied simultaneously.”
Geometric isomorphism and minimum aberration for factorial designs with quantitative factors (2004, background): “Independently, Ye (1999) also observed that level permutation could alter the aliasing structure of designs when linear-quadratic decomposition [see Wu and Hamada (2000), Section 5.6] is used.”
Recent advances in surrogate-based optimization (2009, background): “The linear and quadratic effects can be defined using orthogonal polynomial coding [85] and, with variables scaled ∈ [0, 1], are given by”
Level set based robust shape and topology optimization under random field uncertainties (2010, methodology): “1 Robust design models Conventional robust design, pioneered by Taguchi [27], refers to a class of methods for improving quality and reliability by designing a product or process so that it is robust (insensitive) against variations in uncontrollable noise variables [28-30].”
Sampling in ecology and evolution – bridging the gap between theory and practice (2010, methodology): “A derived, more complex sampling design can then be based on the first results, such as surface response methodology (Box and Hunter 1957, Wu and Hamada 2000), from which we derived our model-based design.”