Design of Experiments in Chemical Engineering. A Practical Guide

  • ID: 2183050
  • Book
  • 620 Pages
  • John Wiley and Sons Ltd
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While existing books related to DOE are focused either on process or mixture factors or analyze specific tools from DOE science, this text is structured both horizontally and vertically, covering the three most common objectives of any experimental research:

∗ screening designs

∗ mathematical modeling, and

∗ optimization.

Dealing with three different type of factors:

∗ Process Factors

∗ Mixture Factors

∗ Process and Mixture Factors combined together.

Written in a simple and lively manner and backed by current chemical product studies from all around the world, the book elucidates basic concepts of statistical methods, experiment design and optimization techniques as applied to chemistry and chemical engineering. Throughout, the focus is on unifying the theory and methodology of optimization with well–known statistical and experimental methods.

The author draws on his own experience in research and development resulting in a work that will assist students, scientists and engineers in using the concepts covered here in seeking optimum conditions for a chemical system or process.

With 441 tables, 250 diagrams, as well as 200 examples drawn from current chemical product studies.

We are convinced that this is an invaluable and convenient source of helpful information for all those involved in the optimization of processes.
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Preface

I INTRODUCTION TO STATISTICS FOR ENGINEERS

Basic Distributions of Discrete and Continual Random Variables

Statistical Inference

Statistical Estimation

Tests and Estimates on Statistical Variance

Analysis of Variance

Regression Analysis

Correlation Analysis

References

II DESIGN AND ANALYSIS OF EXPERIMENTS

Introduction to Design of Experiments–Doe

Preliminary Examination of Subject of Research

Basic Experiment–Mathematical Modeling

Statistical Analysis of Experimental Results

Experimental Optimization of Research Subject

Canonical Analysis of the Response Surface

Examples of Complex Optimizations

References

III MIXTURE DESIGN

Screening Designs

Simplex Lattice Design

Scheffe Simplex Lattice Design

Simplex Centroid Design

Extreme Vertices Design

D–Optimal Design

Draper–Lawrence Design

Full Factorial Mixture Design

Crossed Design–Full Factorial Combined with Mixture Design

Examples of Complex Optimization Mixture Problems

References

IV APPENDIX

Answers to Selected Problems

Tables of Statistical Functions
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"covers the basic theory of DOE and provides numerous practical examples of its application in the chemical process industries"

Organic Process Research and Development, January 2005

"... a useful textbook for a graduate–level course in the statistics of experimental design."

E–STREAMS

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