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    1. Data och IT
    2. Systemvetenskap och AI
    3. Artificiell intelligens

    Artificial Intelligence in Manufacturing

    Concepts and Methods

    AvMasoud Soroush,Richard D Braatz

    Häftad, Engelska, 2024

    1 933 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    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.



    • Presents AI concepts from the computer science field using language and examples designed to inspire engineering graduates
    • Provides worked examples throughout to help readers fully engage with the methods described
    • Includes concepts that are supported by definitions for key terms and chapter summaries

    Produktinformation

    • Utgivningsdatum:2024-01-25
    • Mått:152 x 229 x 19 mm
    • Vikt:610 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:372
    • Förlag:Elsevier Science
    • ISBN:9780323991346

    Utforska kategorier

    • Artificiell intelligens inom Data och IT
    • Tillverkningsteknik inom Naturvetenskap och teknik

    Mer om författaren

    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. 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.

    Innehållsförteckning

    • 1. Data‐driven Physics‐based Digital Twins2. Hybrid Modeling Approach Integrating PLS Models with First-principles Knowledge3. Dynamical Systems-Guided Learning of PDEs from Data4. Learning First-principles Knowledge from Data5. Actual Learning through Machine Learning6. Iterative Cross Learning7. Learning an Algebraic Model from Data8. Data‐driven Optimization Algorithms9. Interpretable Machine Learning10. Learning Science and Algorithms11. Reinforcement Learning12. Machine Learning: Trends, Perspectives, and Prospects13. Artificial Intelligence: Trends, Perspectives, and Prospects14. Artificial Intelligence Education for Chemical Engineers