Data Science in Metal Forming - Wang, Li-Liang; Liu, Heli
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Data Science in Metal Forming provides readers with a framework to collect, visualize, analyze, and characterize metal forming metadata enabling improved design, more efficient production, and more effective application of a range of metals. The first two chapters of the book provide an introduction to the concepts to be covered, including various metal forming technologies, industry 4.0, digital manufacturing, and more. The next chapter features case studies of metal forming data collection spanning several essential procedures and includes data preprocessing and processing methods as well as…mehr

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Produktbeschreibung
Data Science in Metal Forming provides readers with a framework to collect, visualize, analyze, and characterize metal forming metadata enabling improved design, more efficient production, and more effective application of a range of metals. The first two chapters of the book provide an introduction to the concepts to be covered, including various metal forming technologies, industry 4.0, digital manufacturing, and more. The next chapter features case studies of metal forming data collection spanning several essential procedures and includes data preprocessing and processing methods as well as data management techniques. The following chapters outline methods for data processing when lacking essential information, data visualization techniques, insight into how to analyze data from various metal forming processes (stamping, hydroforming, incremental, extrusion, and more), and the book concludes with details on how readers can setup, manage, and most effectively apply their own data repositories.
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Autorenporträt
LiLiang Wang is Head of the Metal Forming and Modeling Group in the Department of Mechanical Engineering, Imperial College. He received his PhD degree from Delft University of Technology. He joined Imperial College in 2009. Dr Wang's major research interests include the design and development of advanced metal forming technologies and manufacturing system. His work has made fundamental contributions to characterization and modelling of materials and interfacial behaviors of engineering materials. Particularly, Dr Wang's research has direct impacts on sustainable manufacturing, e.g., Hot stamping of Aluminum alloy (International Journal of Machine Tools and Manufacture 87, 39-48); Data sciences in metal forming (Nat. Commun., 2022, 13: 5748,); novel lightweight forming technology: FAST (Int. J. Plast., 2019, 119: 230-248); Tribology in metal forming (Friction 10 (6), 911-926) and innovative material characterization techniques (Addit. Manuf. 2021, 37: 101720).