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Design of Experiments in Chemical Engineering: A Practical Guide

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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.

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.

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