This book presents modern applications of Response Surface Methodology (RSM) in engineering science. Chapters discuss such topics as machine learning models of RSM as well as potential applications of RSM in industries such as pharmaceuticals, agriculture, textiles, and food, among others. Contents 1. Introductory Chapter: Response Surface Methodology in Engineering Science 2. Introducing Machine Learning Models to Response Surface Methodologies 3. Global Optimization Method to Multiple Local Optimals with the Surface Approximation Methodology and Its Application for Industry Problems 4. Response Surface Designs Robust against Nuisance Factors 5. Central Composite Design for Response Surface Methodology and Its Application in Pharmacy 6. Response Surface Methodology Optimization in Asphalt Mixtures: A Review 7. Application of Response Surface Method for Analyzing Pavement Performance 8. Selection of Optimal Processing Condition during Removal of Methylene Blue Dye Using Treated Betel Nut Fibre Implementing Desirability Based RSM Approach 9. Uses of the Response Surface Methodology for the Optimization of Agro-Industrial Processes 10. In Search of Optimal Laser Settings for Lithotripsy by Numerical Response Surfaces of Ablation and Retropulsion 11. Response Surface Methodology Applied to the Optimization of Phenolic Compound Extraction from Brassica 12. Practicing Response Surface Designs in Textile Engineering: Yarn Breaking Strength Exercise 13. Application of Response Surface Methodology in Food Process Modeling and Optimization

Response Surface Methodology in Engineering Science PDF

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