Artificial Intelligence in Manufacturing: Applications and Case Studies provides detailed technical descriptions of emerging applications of AI in manufacturing using case studies to explain implementation. Artificial intelligence is increasingly being applied to all engineering disciplines, producing insights into how we understand the world and allowing us to create products in new ways. This book unlocks the advantages of this technology for manufacturing by drawing on work by leading researchers who have successfully used it in a range of applications. Processes including additive manufacturing, pharmaceutical manufacturing, painting, chemical engineering and machinery maintenance are all addressed.
Case studies, worked examples, basic introductory material and step-by-step instructions on methods make the work accessible to a large group of interested professionals.
1. Artificial Intelligence in Manufacturing - p. i 2. Cover - p. i 3. Halftitle Page - p. ii 4. Title Page - p. iii 5. Copyright Page - p. iv 6. Table of Contents - p. iv 7. Contributors - p. ix 8. Preface - p. xi 9. Chapter 1 Artificial intelligence for paints/coatings manufacturing - p. 1 10. Chapter 2 Data-driven discovery and design of additives for controlled polymer morphology and performance - p. 29 11. Chapter 3 Data, machine learning, first-principles, and hybrid models in the petrochemical industry - p. 57 12. Chapter 4 Perspectives on artificial intelligence for plasma-assisted manufacturing in semiconductor industry - p. 97 13. Chapter 5 Machine learning in reaction engineering - p. 139 14. Chapter 6 Artificial intelligence in catalysis - p. 167 15. Chapter 7 Advanced manufacturing of touch-sensitive textiles - p. 205 16. Chapter 8 Cyber–physical systems framework for AI in smart manufacturing and maintenance - p. 233 17. Chapter 9 Dynamic data feature engineering for process operation troubleshooting - p. 273 18. Chapter 10 Advanced manufacturing of biopharmaceuticals - p. 299 19. Index - p. 323
Artificial Intelligence in Manufacturing: Applications and Case Studies provides detailed technical descriptions of emerging applications of AI in manufacturing using case studies to explain implementation. Artificial intelligence is increasingly being applied to all engineering disciplines, producing insights into how we understand the world and allowing us to create products in new ways. This book unlocks the advantages of this technology for manufacturing by drawing on work by leading researchers who have successfully used it in a range of applications. Processes including additive manufacturing, pharmaceutical manufacturing, painting, chemical engineering and machinery maintenance are all addressed.
Case studies, worked examples, basic introductory material and step-by-step instructions on methods make the work accessible to a large group of interested professionals.
1. Artificial Intelligence in Manufacturing - p. i 2. Cover - p. i 3. Halftitle Page - p. ii 4. Title Page - p. iii 5. Copyright Page - p. iv 6. Table of Contents - p. iv 7. Contributors - p. ix 8. Preface - p. xi 9. Chapter 1 Artificial intelligence for paints/coatings manufacturing - p. 1 10. Chapter 2 Data-driven discovery and design of additives for controlled polymer morphology and performance - p. 29 11. Chapter 3 Data, machine learning, first-principles, and hybrid models in the petrochemical industry - p. 57 12. Chapter 4 Perspectives on artificial intelligence for plasma-assisted manufacturing in semiconductor industry - p. 97 13. Chapter 5 Machine learning in reaction engineering - p. 139 14. Chapter 6 Artificial intelligence in catalysis - p. 167 15. Chapter 7 Advanced manufacturing of touch-sensitive textiles - p. 205 16. Chapter 8 Cyber–physical systems framework for AI in smart manufacturing and maintenance - p. 233 17. Chapter 9 Dynamic data feature engineering for process operation troubleshooting - p. 273 18. Chapter 10 Advanced manufacturing of biopharmaceuticals - p. 299 19. Index - p. 323
