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…mehr
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. Machine Learning in Paints and Coatings 2. Machine Learning in Lithium-ion Batteries 3. Machine Learning for Emerging Two-phase Cooling Technologies 4. Algorithm-driven Design of Composite Materials Realized through Additive Manufacturing 5. Machine-learning-based Monitoring of Laser Powder Bed Fusion 6. Data Analytics and Cyber-physical Systems for Maintenance and Service Innovation 7. Machine Learning in Catalysis 8. Artificial Intelligence in Petrochemical Industry 9. Machine Learning-assisted Plasma Medicine 10. Dynamic Data Feature Engineering for Process Operation Troubleshooting 11. Geometric Structure-Property Relationships Captured by Theory-Guided, Interpretable Machine Learning 12. Molecular Design Blueprints from Machine Learning for Catalysts and Materials 13. Physics-driven Machine Learning for Characterizing Surface Microstructure of Complex Materials 14. Process Performance Assessment Using Machine Learning 15. Artificial Intelligence in Chemical Engineering 16. Production of Polymer Films with Optimal Properties Using Machine Learning
1. Machine Learning in Paints and Coatings 2. Machine Learning in Lithium-ion Batteries 3. Machine Learning for Emerging Two-phase Cooling Technologies 4. Algorithm-driven Design of Composite Materials Realized through Additive Manufacturing 5. Machine-learning-based Monitoring of Laser Powder Bed Fusion 6. Data Analytics and Cyber-physical Systems for Maintenance and Service Innovation 7. Machine Learning in Catalysis 8. Artificial Intelligence in Petrochemical Industry 9. Machine Learning-assisted Plasma Medicine 10. Dynamic Data Feature Engineering for Process Operation Troubleshooting 11. Geometric Structure-Property Relationships Captured by Theory-Guided, Interpretable Machine Learning 12. Molecular Design Blueprints from Machine Learning for Catalysts and Materials 13. Physics-driven Machine Learning for Characterizing Surface Microstructure of Complex Materials 14. Process Performance Assessment Using Machine Learning 15. Artificial Intelligence in Chemical Engineering 16. Production of Polymer Films with Optimal Properties Using Machine Learning
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