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Design of Experiments (DOE) in Chemical Engineering

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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.

Product Details

Table of Contents

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

About the Author

Zivorad R. Lazic is Quality Assurance Manager at Lenzing Fibers Corporation, Lowland, Tennessee, USA. Born in Ljubovija, Serbia, he completed his studies at Belgrade University, writing his thesis under the supervision of Prof. Dragoljub Vukovic. He began his career in Belgrade at the Military Technical Institute (VTI), where he was Head of Department for R&D into composite rocket propellants. He was trained at Hercules Inc., McGregor, TX, and spent more than six years as Vice President for Process and Product Development in P.T. South Pacific Viscose, Indonesia from 1994 until 2001. Dr. Lazic's interests include advanced statistical tools, DOE, SPC, EVOP, neural network modeling and the six-sigma approach.


" a useful textbook for a graduate-level course in the statistics of experimental design." ( E-STREAMS, September 2005) "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)

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