1st Edition

Experimental Design and Process Optimization

    336 Pages 158 B/W Illustrations
    by CRC Press

    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.

    Initial Considerations

    Topics of Elementary Statistics

    Introductory Notions

    General Ideas


    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


    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)


    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


    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




    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.