Emerging processes, machine learning and applications in composite additive manufacturing

Materials Advances 2026 Open access

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Authors: Md Zillur Rahman, H K Mahedi Azad, Morad Hossain Diganto
DOI: 10.1039/d6ma00219f
Cited by: 1
References: 204

Abstract

Composite AM performance is governed by reinforcement dispersion and orientation, interfacial bonding, porosity, and anisotropy; ML-enabled sensing, benchmarking, digital twins, and uncertainty-aware digital threads enable qualification-ready CAM.

Fields of Study & Subjects

Additive Manufacturing and 3D Printing Technologies Machine Learning in Materials Science Additive Manufacturing Materials and Processes

Publication details

Journal / source
Materials Advances
Publisher
Royal Society of Chemistry (RSC)
Volume
7
Issue
15
Pages
7423–7466
Publication date
1 January 2026
Language
EN