Recent developments in the application of machine-learning towards accelerated predictive multiscale design and additive manufacturing

Sandeep Suresh Babu, Abdel Hamid I. Mourad, Khalifa H. Harib, Sanjairaj Vijayavenkataraman

Research output: Contribution to journalReview articlepeer-review

13 Citations (Scopus)

Abstract

The application of three-dimensional (3D) printing/Additive Manufacturing (AM) for developing multi-functional smart/intelligent composite materials is a highly promising area of engineering research. However, there is often no reliable means for predicting and modelling the material performance, and the wide-scale industrial adoption of AM is limited due to factors such as design barriers, limited materials library, processing defects and inconsistency in product quality. A comprehensive framework considering the generalised applicability of ML algorithms at sub-sequent stages of the AM process from the initial design to the post-processing stages in the literature is lacking. In this paper, the integration of various ML applications at various sub-processes is discussed, including pre-processing design stage, parameter optimisation, anomaly detection, in-situ monitoring, and the final post-processing stages. The challenges and potential solutions for standardising these integrated techniques have been identified. The article is promising for professionals and researchers in AM and AI/ML techniques.

Original languageEnglish
Article numbere2141653
JournalVirtual and Physical Prototyping
Volume18
Issue number1
DOIs
Publication statusPublished - 2023

Keywords

  • 3D printing
  • Machine learning
  • additive manufacturing
  • fused deposition modelling
  • multiscale modelling
  • smart materials

ASJC Scopus subject areas

  • Signal Processing
  • Modelling and Simulation
  • Computer Graphics and Computer-Aided Design
  • Industrial and Manufacturing Engineering

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