Digital Twins in Manufacturing
Applications and Case Studies
- 1st Edition - October 1, 2026
- Latest edition
- Editors: Masoud Soroush, Richard D Braatz
- Language: English
Digital Twins in Manufacturing: Applications and Case Studies explores digital twin technologies, demonstrating how digital twins enhance manufacturing processes, optimize effici… Read more
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Description
Description
Digital Twins in Manufacturing: Applications and Case Studies explores digital twin technologies, demonstrating how digital twins enhance manufacturing processes, optimize efficiency, and facilitate informed decision-making. By bridging the gap between theoretical knowledge and practical implementation, the book equips professionals with the tools needed to leverage digital twins for improved product quality and operational effectiveness. It covers a wide array of topics, including digital twins for biomanufacturing, polymerization processes, additive manufacturing, and energy industries. Readers will find detailed discussions on predictive maintenance, process optimization, and the integration of AI and IoT strategies.
Each chapter presents actionable insights and step-by-step implementation guides, addressing real-world challenges and showcasing successful applications in smart factories and high-risk environments. By bridging the gap between theoretical knowledge and practical implementation, the book equips professionals with the tools needed to leverage digital twins for improved product quality and operational effectiveness.
Each chapter presents actionable insights and step-by-step implementation guides, addressing real-world challenges and showcasing successful applications in smart factories and high-risk environments. By bridging the gap between theoretical knowledge and practical implementation, the book equips professionals with the tools needed to leverage digital twins for improved product quality and operational effectiveness.
Key features
Key features
- Includes real-world case studies
- Presents a step-by-step implementation guide
- Outlines predictive maintenance and process optimization techniques
- Discusses AI and IoT integration strategies
- Forecasts future trends and innovations in digital twin technology
Readership
Readership
Graduate students; researchers and instructors in academia, national labs, and manufacturing industries; mechanical, systems and manufacturing engineers; and professionals in industries that use or apply digital twins
Table of contents
Table of contents
1. Digital twins for biomanufacturing
2. Digital twins for polymerization processes
3. Digital twins in additive manufacturing
4. Digital twins in sheet and film processes
5. Digital Twins in three-dimensional printing
6. Digital twins in small-molecule drug manufacturing
7. Digital twins in petroleum and petrochemical industries
8. Digital twins in energy industries
9. Digital twins in action
10. Introduction to Digital Twin Applications in Industrial Manufacturing
11. Practical Use Cases for Digital Twins in Product Development
12. Optimizing Manufacturing Operations with Digital Twins
13. Digital Twins for Asset Management and Maintenance
14. Improving Quality Control and Assurance Using Digital Twins
15. Supply Chain Applications of Digital Twin Technology
16. Leveraging Digital Twins for Product Customization and Personalization
17. Sustainability and Energy Efficiency through Digital Twins
18. Human-Centric Digital Twins: Enhancing Worker Safety and Productivity
19. Collaboration and Ecosystem Development with Digital Twins
20. Digital Twin Applications in Smart Factories and Industry 4.0
21. Digital Twins in High-Risk Manufacturing Environments
22. Scaling Digital Twin Solutions: Lessons from Industry Leaders
23. Real-World Challenges in Digital Twin Implementation
24. The Future of Digital Twin Applications in Manufacturing
2. Digital twins for polymerization processes
3. Digital twins in additive manufacturing
4. Digital twins in sheet and film processes
5. Digital Twins in three-dimensional printing
6. Digital twins in small-molecule drug manufacturing
7. Digital twins in petroleum and petrochemical industries
8. Digital twins in energy industries
9. Digital twins in action
10. Introduction to Digital Twin Applications in Industrial Manufacturing
11. Practical Use Cases for Digital Twins in Product Development
12. Optimizing Manufacturing Operations with Digital Twins
13. Digital Twins for Asset Management and Maintenance
14. Improving Quality Control and Assurance Using Digital Twins
15. Supply Chain Applications of Digital Twin Technology
16. Leveraging Digital Twins for Product Customization and Personalization
17. Sustainability and Energy Efficiency through Digital Twins
18. Human-Centric Digital Twins: Enhancing Worker Safety and Productivity
19. Collaboration and Ecosystem Development with Digital Twins
20. Digital Twin Applications in Smart Factories and Industry 4.0
21. Digital Twins in High-Risk Manufacturing Environments
22. Scaling Digital Twin Solutions: Lessons from Industry Leaders
23. Real-World Challenges in Digital Twin Implementation
24. The Future of Digital Twin Applications in Manufacturing
Product details
Product details
- Edition: 1
- Latest edition
- Published: October 1, 2026
- Language: English
About the editors
About the editors
MS
Masoud Soroush
Masoud Soroush is the George B. Francis Chair Professor of Engineering at Drexel University and directs the Future Layered nAnomaterials Knowledge and Engineering (FLAKE) Consortium, collaborating with over 30 researchers from Drexel, the University of Pennsylvania, and Purdue. He has held positions as a Visiting Scientist at DuPont and a Visiting Professor at Princeton. An Elected Fellow of AIChE and Senior Member of IEEE, Soroush has received numerous awards, including the AIChE 2023 Excellence in Process Development Research Award. He holds a BS from Abadan Institute of Technology and MS/PhD degrees from the University of Michigan, with research focusing on advanced manufacturing and nanomaterials.
Affiliations and expertise
Professor of Chemical and Biological Engineering, Drexel University, Philadelphia, PA, USARD
Richard D Braatz
Dr. Richard D. Braatz is the Edwin R. Gilliland Professor of Chemical Engineering at MIT, specializing in advanced manufacturing systems. His research focuses on process data analytics, mechanistic modeling, and robust control systems, particularly in monoclonal antibody, vaccine, and gene therapy production. He holds an M.S. and Ph.D. from Caltech and previously served as a professor at the University of Illinois and a visiting scholar at Harvard. Dr. Braatz has received several prestigious awards, including the Donald P. Eckman Award and the Curtis W. McGraw Research Award, and is a Fellow of multiple professional organizations and a member of the U.S. National Academy of Engineering.
Affiliations and expertise
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, USA