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Design of Experiments

  1. Sergio Soravia1,
  2. Andreas Orth2

Published Online: 15 APR 2009

DOI: 10.1002/14356007.e08_e01.pub3

Ullmann's Encyclopedia of Industrial Chemistry

Ullmann's Encyclopedia of Industrial Chemistry

How to Cite

Soravia, S. and Orth, A. 2009. Design of Experiments. Ullmann's Encyclopedia of Industrial Chemistry. .

Author Information

  1. 1

    Process Technology, Degussa AG, Hanau, Germany

  2. 2

    University of Applied Sciences, Frankfurt am Main, Germany

Publication History

  1. Published Online: 15 APR 2009


The article contains sections titled:

1.1.General Remarks
1.2.Application in Industry
1.3.Historical Sidelights
1.4.Aim and Scope
2.Procedure for Conducting Experimental Investigations: Basic Principles
2.1.System Analysis and Clear Definition of Objectives
2.2.Response Variables and Experimental Factors
2.3.Replication, Blocking, and Randomization
2.5.Different Experimental Strategies
2.6.Drawback of the One-Factor-at-a-Time Method
3.Factorial Designs
3.1.Basic Concepts
3.2.The 22 Factorial Design
3.3.The 23 Factorial Design
3.4.Fractional Factorial Designs
4.Response Surface Designs
4.1.The Idea of Using Basic Empirical Models
4.2.The Class of Models Used in DoE
4.3.Standard DoE Models and Corresponding Designs
4.4.Using Regression Analysis to Fit Models to Experimental Data
5.Methods for Assessing, Improving, and Visualizing Models
5.1.R2 Regression Measure and Q2 Prediction Measure
5.2.ANOVA (Analysis of Variance) and Lack-of-Fit Test
5.3.Analysis of Observations and Residuals
5.4.Heuristics for Improving Model Performance
5.5.Graphical Visualization of Response Surfaces
6.Optimization Methods
6.1.Basic EVOP Approach Using Factorial Designs
6.2.Model-Based Approach
6.3.Multi-Response Optimization with Desirability Functions
6.4.Validation of Predicted Optima
7.Designs for Special Purposes
7.1.Mixture Designs
7.2.Designs for Categorical Factors
7.3.Optimal Designs
7.4.Robust Design as a Tool for Quality Engineering