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Autor(en): 
  • Kunpeng Zhu
  • Ying-Hsi Jerry Fuh
  • Monitoring and Control of Laser Additive Manufacturing Process: Theory and Applications 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   i.d.R. innert 7-14 Tagen versandfertig
    Veröffentlichung:  Mai 2026  
    Genre:  Naturwissensch., Medizin, Technik 
     
    Additive Manufacturing / Control, Robotics, Automation / Defect Detection / Industrial and Production Engineering / Laser addictive manufacturing process / Laser Technology / Lasertechnik und Holographie / machine learning
    ISBN:  9789819552252 
    EAN-Code: 
    9789819552252 
    Verlag:  Springer EN 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 235 mm / B 155 mm / D  
    Seiten:  635 
    Illustration:  XXI, 635 p. 355 illus., 242 illus. in color., schwarz-weiss Illustrationen, farbige Illustrationen 
    Zus. Info:  EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025. 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    This book aims to develop methodologies for enhancing the build quality, automation, and productivity of laser-based additive manufacturing (LAM) systems. Effective online monitoring and intelligent process control methods provide the technical foundation for realizing such advanced LAM systems. Following a comprehensive introduction to LAM processes, including process classifications, process design, material considerations, and molten pool dynamics, the book presents a general framework for the design and implementation of an intelligent LAM monitoring system. Adopting a data-driven approach, the book elaborates on state-of-the-art techniques in measurement, signal processing, and machine learning for process monitoring and intelligent control, with the goal of improving quality, reliability, and production efficiency. Within this framework, both fundamental theories and recent advances in machine vision, deep learning, and digital twin technologies for LAM systems are introduced and discussed. The book includes over 120 figures and diagrams to illustrate key concepts and results. It integrates the author’s research and teaching experience in the field and serves as a valuable reference for researchers, graduate students, and engineers, as well as a supplementary resource for advanced undergraduate students.

      



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