Fr. 236.00

Advanced Manufacturing Methods - Smart Processes and Modeling for Optimization

English · Hardback

Shipping usually within 3 to 5 weeks

Description

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Advanced Manufacturing Methods: Smart Processes and Modeling for Optimization describes developments in advanced manufacturing processes and applications considering typical and advanced materials. It helps readers implement manufacturing 4.0 production techniques and highlights why a consolidated source and robust platform are necessary for implementing machine learning processes in the manufacturing sector.

Discusses the industrial impact of manufacturing process

Provides novel fundamental manufacturing solutions

Presents the various aspects of applications in advanced materials in correlation of physical properties with macro-, micro- and nanostructures

Reviews both classical and artificial manufacturing when applied with typical and novel innovative materials

Aimed at those working in manufacturing, mechanical and optimization of manufacturing processes, this work provides readers with a comprehensive view of current development in, and applications of, advanced manufacturing.

List of contents

Preface, Editor Biographies, List of Contributors, Chapter 1. Enabling Smart Manufacturing with Artificial Intelligence and Big Data: A Survey and Perspective, Chapter 2. Green Applications with an Advanced Manufacturing Method: Cold Spray Deposition Technology, Chapter 3. Multi-Criteria Decision-Making Applications in Conventional and Unconventional Machining Techniques, Chapter 4. Taguchi-Based GRA Method for Multi-Response Optimization of Spool Bore in EHSV Made Up of Stainless Steel, Chapter 5. Wearing Behaviour of Electrodes during EDM of AISI 1035 Steel, Chapter 6. Achieving Optimal Efficiency in Manufacturing through Reinforced PA 3D Printed Parts Generated by FDM Technology, Chapter 7. Characterization of Effect of Cellular Support Structures in Selective Laser Melting Using Stainless Steel, Chapter 8. Using Carbon Nanotubes for Advanced Manufacturing of Antibiofilm Materials, Chapter 9. Development of a Novel Nanocomposite Coating for Tribological Applications, Index

About the author

Dr. Catalin Pruncu has been a Charter and Member of the Institute of Mechanical Engineers (UK) since November 2015. Currently, his research is dedicated to further develop and validate hot form quench (HFQ®) Technology for use in the global automotive industry. Dr. Pruncu is Research Association at Imperial College London.
Dr. Jamal Zbitou received the Ph.D. degree in electronics from Polytech of Nantes, the University of Nantes, France in 2005. He is currently Associate Professor of Electronics at FST, Hassan First University, Settat, Morocco and the head of Computing Networks and Telecommunication at the MEET Laboratory, FSTS. He is involved in the design of hybrid, monolithic active, and passive microwave electronic circuits.

Summary

The book describes advanced manufacturing processes and applications in design of electrical equipment. It helps readers implement manufacturing 4.0 production techniques and highlights why a consolidated source and robust platform are necessary for implementing machine learning processes.

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