Artificial Intelligence in Manufacturing: Concepts and Methods

— —

Masoud Soroush (Professor of Chemical and Biological Engineering, Drexel University, Philadelphia, PA, USA) Richard D Braatz (Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, USA)

Artificial Intelligence in Manufacturing

Concepts and Methods

Masoud Soroush (Professor of Chemical and Biological Engineering, Drexel University, Philadelphia, PA, USA), Richard D Braatz (Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, USA)

$352.95

Paperback

Not in-store but you can order this
How long will it take?

Availability Information

We source books from suppliers in Australia and overseas. For books we don't currently have in stock, the time it takes to get them from our suppliers can vary widely - from a few days to a few months - so we check each book with each supplier to determine the expected time it will take to be supplied to us.

We then advise you accordingly. If the time taken to get any book is too long for you, you can let us know and we will cancel or adjust your order, and refund as required.

To find out the anticipated arrival time for specific items prior to ordering, please contact us by phone or email:

Phone +61 2 9264 3111, or 1800 4 BOOKS (1800 4 26657) if outside Sydney:
option 1 Abbey's Bookshop (Crime, History, Science, Kids & more) • info@abbeys.com.au
option 2 Language Book Centre (ESL & Foreign Languages) • language@abbeys.com.au
option 3 Galaxy Bookshop (Sci-fi, Fantasy, Romance, Graphic Novels) • sf@galaxybooks.com.au

QTY:

English

Academic Press Inc
26 January 2024

Industrial chemistry & manufacturing technologies; Other manufacturing technologies; Artificial intelligence

Artificial Intelligence in Manufacturing: Concepts and Methods explains the most successful emerging techniques for applying AI to engineering problems. Artificial intelligence is increasingly being applied to all engineering disciplines, producing more 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 developed methods that can apply to a range of engineering applications.

The book addresses educational challenges needed for widespread implementation of AI and also provides detailed technical instructions for the implementation of AI methods. Drawing on research in computer science, physics and a range of engineering disciplines, this book tackles the interdisciplinary challenges of the subject to introduce new thinking to important manufacturing problems.

Edited by: Masoud Soroush (Professor of Chemical and Biological Engineering Drexel University Philadelphia PA USA), Richard D Braatz (Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, USA)
Imprint: Academic Press Inc
Country of Publication: United Kingdom
Dimensions: Height: 229mm, Width: 152mm,
Weight: 610g
ISBN: 9780323991346
ISBN 10: 0323991343
Pages: 372
Publication Date: 26 January 2024
Audience: Professional and scholarly , Undergraduate
Format: Paperback
Publisher's Status: Active

1. Data-driven Physics-based Digital Twins 2. Hybrid Modeling Approach Integrating PLS Models with First-principles Knowledge 3. Dynamical Systems-Guided Learning of PDEs from Data 4. Learning First-principles Knowledge from Data 5. Actual Learning through Machine Learning 6. Iterative Cross Learning 7. Learning an Algebraic Model from Data 8. Data-driven Optimization Algorithms 9. Interpretable Machine Learning 10. Learning Science and Algorithms 11. Reinforcement Learning 12. Machine Learning: Trends, Perspectives, and Prospects 13. Artificial Intelligence: Trends, Perspectives, and Prospects 14. Artificial Intelligence Education for Chemical Engineers

Masoud Soroush is a professor of chemical and biological engineering at Drexel University. He received his B.S. in chemical engineering from Abadan Institute of Technology, Iran, and M.S.E. degrees in chemical engineering and electrical engineering and Ph.D. in chemical engineering from the University of Michigan, Ann Arbor, United States. He was a visiting scientist at DuPont Marshall Lab, Philadelphia, 2002–2003 and a visiting professor at Princeton University in 2008. He was the AIChE Area 10b Program Coordinator in 2009, and the AIChE Director on the American Automatic Control Council Board of Directors from 2010–2013. His awards include the U.S. National Science Foundation Faculty Early CAREER Award in 1997 and the O. Hugo Schuck Best Paper Award of American Automatic Control Council in 1999. He is an elected fellow of AIChE and a senior member of IEEE. His research interests are in process systems engineering, polymer reaction engineering, electronic-level modeling of reactions, polymer membranes, multiscale modeling, probabilistic modeling and inference, and renewable power generation and storage systems. He has authored or co-authored more than 320 publications, including over 180 refereed papers. Richard D Braatz works in the Department of Chemical Engineering at Massachusetts Institute of Technology, Cambridge, USA.