Skip to main content

Machine Learning for Powder-Based Metal Additive Manufacturing

  • 1st Edition - November 1, 2024
  • Editors: Gurminder Singh, Farhad Imani, Asim Tewari, Sushil Mishra
  • Language: English
  • Paperback ISBN:
    9 7 8 - 0 - 4 4 3 - 2 2 1 4 5 - 3
  • eBook ISBN:
    9 7 8 - 0 - 4 4 3 - 2 2 1 4 6 - 0

Machine Learning for Powder-based Metal Additive Manufacturing outlines machine learning (ML) methods for additive manufacturing (AM) of metals that will improve product quality,… Read more

Machine Learning for Powder-Based Metal Additive Manufacturing

Purchase options

Limited Offer

Save 50% on book bundles

Immediately download your ebook while waiting for your print delivery. No promo code is needed.

Book bundle cover eBook and print

Institutional subscription on ScienceDirect

Request a sales quote

Machine Learning for Powder-based Metal Additive Manufacturing outlines machine learning (ML) methods for additive manufacturing (AM) of metals that will improve product quality, optimize manufacturing processes, and reduce costs. The book combines ML and AM methods to develop intelligent models that train AM techniques in pre-processing, process optimization, and post-processing for optimized microstructure, tensile and fatigue properties, and biocompatibility for various applications. The book covers ML for design in AM, ML for materials development and intelligent monitoring in metal AM, both geometrical deviation and physics informed machine learning modeling, as well as data-driven cost estimation by ML.

In addition, optimization for slicing and orientation, ML to create models of materials for AM processes, ML prediction for better mechanical and microstructure prediction, and feature extraction by sensing data are all covered, and each chapter includes a case study.