Preface

Response Surface Methodology (RSM) is one of the major methodologies for analysts but not so much for engineers and scientists. However, there has been a paradigm shift and, as such, this book explores the use of RSM in engineering science.

The book includes thirteen chapters with case studies that discuss the basics of RSM and its potential uses and applications in engineering science. Chapter 1 provides an introduction to RSM in engineering science and Chapter 2 discusses machine learning models of RSM.

Chapter 3 highlights the global optimization and surface approximation methodologies along with the applications to eliminate the industrial problems. Chapter 4 centers on response surface design robust against nuisance factors. Chapter 5 deals with the central composite design (CCD) for RSM for possible application in pharmacy. Chapter 6 discusses RSM optimization in asphalt mixtures. Chapter 7 examines the application of RSM for analyzing pavement performance. Chapter 8 emphasizes the optimal condition selection for removal of methylene blue dye implementing a desirability-based RSM approach. Chapter 9 talks about how RSM can be used to optimize agro-industrial processes. Chapter 10 covers optimal laser settings for lithotripsy by numerical response surfaces of ablation and retropulsion. Chapter 11 calls attention to RSM applied to optimize phenolic compound extraction from Brassica. Chapter 12 discusses response surface designs in textile engineering, and Chapter 13 concludes with an overview of the use of RSM in food process modeling and optimization.

This volume is designed to counter the notion that RSM is only useful for analysts. It is a useful resource for readers interested in this methodology and those who wish to use it in new and innovative research.

> **Palanikumar Kayaroganam** Department of Mechanical Engineering, Sri Sai Ram Institute of Technology, Chennai, India

Section 1 Introduction

#### **Chapter 1**
