Full Scale Plant Optimization in Chemical Engineering: A Practical Guide
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Highlights the basic principles and applications of the primary three methods in plant and process optimization for responsible operators and engineers.
Chemical engineers are a vital part of the creation of any process development—lab-scale and pilot-scale—for any plant. In fact, they are the lynchpin of later efforts to scale-up and full-scale plant process improvement. As these engineers approach a new project, there are three generally recognized methodologies that are applicable in industry generally: Design of Experiments (DOE), Evolutionary Operations (EVOP), and Data Mining Using Neural Networks (DM).
In Full Scale Plant Optimization in Chemical Engineering, experienced chemical engineer Živorad R. Laziċ offers an in-depth analysis and comparison of these three methods in full-scale plant optimization applications. The book is designed to provide the basic principles and necessary information for complete understanding of these three methods (DOE, EVOP, and DM). The application of each method is fully described.
Full Scale Plant Optimization in Chemical Engineering readers will also find:
- A thorough discussion of the advantages, disadvantages and applications for the five different EVOP methods (BEVOP, ROVOP, REVOP, QSEVOP & SEVOP) with examples and simulations
- An overview of EVOP tools that responsible operators and engineers utilize in deciding which EVOP method is the most appropriate for the certain type of the process
- Particular attention is given to the simple but powerful technique Evolutionary Operation or EVOP, which provides the experimental tools for the full scale plant optimization
Full Scale Plant Optimization in Chemical Engineering is a useful reference for all chemists in industry, chemical engineers, pharmaceutical chemists, and process engineers.
Autoren-Profil
Živorad R. Laziċ is the author of “Design of Experiments in Chemical Engineering: A Practical Guide”, published by J. Wiley in January 2004. He has produced a unique, “how to do it”, a practical guide for the statistical design of experiments. It is the ideal book for the industrial scientist or engineer who wants to take an advantage of DOE techniques without becoming a statistician. Basic statistical ideas are presented clearly and simply with numerous examples. This is one of the few books that are practically suited for self-study by a busy technologist, engineers and scientists. He is a Certified Six-Sigma Black Belt professional with interests in advanced statistical tools, Design of Experiments(DOE), Statistical Process Control(SPC), Evolutionary Operation(EVOP) and process modeling via application of neural networks.
