Experimental Design and Process Optimization: 1st Edition (Hardback) book cover

Experimental Design and Process Optimization

1st Edition

By Maria Isabel Rodrigues, Antonio Francisco Iemma

CRC Press

336 pages | 158 B/W Illus.

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pub: 2014-12-11
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Description

Experimental Design and Process Optimization delves deep into the design of experiments (DOE). The book includes Central Composite Rotational Design (CCRD), fractional factorial, and Plackett and Burman designs as a means to solve challenges in research and development as well as a tool for the improvement of the processes already implemented. Appropriate strategies for 2 to 32 factors are covered in detail in the book.

The book covers the essentials of statistical science to assist readers in understanding and applying the concepts presented. It also presents numerous examples of applications using this methodology. The authors are not only experts in the field but also have significant practical experience. This allows them to discuss the application of the theoretical aspects discussed through various real-world case studies.

Table of Contents

Initial Considerations

Topics of Elementary Statistics

Introductory Notions

General Ideas

Variables

Populations and Samples

Importance of the Form of the Population

First Ideas of Interference on a Normal Population

Parameters and Estimates

Notions on Testing Hypotheses

Inference of the Mean of a Normal Population

Inference of the Variance of a Normal Population

Inference of the Means of Two Normal Populations

Independent Samples

Paired Samples

Linear Relationship between Two Quantitative Variables

Quantification of a Simple Linear Relationship

Functional Relationship amongst Two Variables

Understanding Factorial Designs

Introductory Concepts

Completely Randomized Experimental Designs with a 2k Factorial Scheme

Factorial 22 with Non-Significant Interaction

The 22 Factorial without Repetitions

Factorial Fractions with Two Level

General Concepts

Half Factorials: ½ Fraction

Quarter Factorials: ¼ Fraction

Comparison of the Methodologies: Study of One Variable at a Time versus Factorial Design

Introduction

Case Study - Evaluation of the Effects of pH and Temperature on the Activity of an Enzyme

Experimental Strategy for Fractional Factorials and the Central Composite Rotational Design (CeRD)

Introduction

Case Study - Experimental Design for 2 Independent Variables

Case Study - Experimental Design for 3 Independent Variables

Case Study - Experimental Design for 4 Independent Variables

Case Study - Experimental Design for 5 Independent Variables

Case Study - Experimental Design for 6 Independent Variables

Case Study - Experimental Design for 7 Independent Variables

Case Study - Experimental Design for 8 Independent Variables

Selection of Variables

Fundamental Theory of the Plackett and Burman (PB) Designs

Locating the Problem

Hadamard Matrices

Some Properties of the Designs

PB Matrix Design

Final Considerations

Matrices of the PB Design

Recommendations

Matrices of the PB Design

Determination of the Main Effects and Calculation of the Deviations for PB Designs

Case Study using PB Design

Case Studies - Applications in Product Processes and Formulations

Case Study - Synthesis of Dextran - Analysis of the Model as from the Coded and Real Values

Case Study - Development of Bread with Substituted Ingredients

Case Study - Alkalization Process of Cocoa Nibs (Theobroma Cacao L.) and Evaluation of Quality

Case Study - Batch Distillation of the Natural Aroma of Cashew Fruit

Case Study - Evaluation of Curvature in Fractionated and/or Plackett and Burman (PB) Designs where the Central Point Responses are Lower or Higher than the Other Treatments

References

Tables

About the Authors

Maria Isabel Rodrigues is a professor at the University of Campinas in Brazil. She received her BS, MS, and PhD degrees in food engineering from the University of Campinas, Brazil. Dr. Rodrigues has taught courses of experimental design and process optimization at a postgraduate level at the University of Campinas, in private companies, and at other universities and institutions. She has worked as a consultant using this statistical tool in various specialty areas such as bioremediation, developments in microbial analytical methods, and fermentation and enzyme processes as well as in the automotive, chemical, petrochemical, cosmetic, pharmaceutical, and food industries.

Antonio Francisco Iemma has been a university-level teacher for more than 40 years. He has taught mathematics and biostatistics at the University of Ribeirão Preto, the Universidade Estadual Paulista, and the University of São Paulo. He received his master’s and doctoral degrees in statistics from the University of São Paulo, Brazil. He did his postdoctoral work at the Faculté Universitaire de Sciences Agronomiques de Gembloux in Belgium. Dr. Iemma has been a visiting lecturer at universities in Brazil and other countries such as Argentina, Belgium, Columbia, Cuba, and France, among others. He is also the former manager of biostatistics in the experiment optimization sector for GlaxoSmithKline Biological in Rixensart in Belgium.

Subject Categories

BISAC Subject Codes/Headings:
SCI013060
SCIENCE / Chemistry / Industrial & Technical
TEC012000
TECHNOLOGY & ENGINEERING / Food Science