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Neural Computing and Applications
Erschienen in: Neural Computing and Applications 20/2022

17.08.2022 | Review

Computational AI models in VAT photopolymerization: a review, current trends, open issues, and future opportunities

verfasst von: Isha Sachdeva, Sivasubramani Ramesh, Utkarsh Chadha, Hruditha Punugoti, Senthil Kumaran Selvaraj

Erschienen in: Neural Computing and Applications | Ausgabe 20/2022

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Abstract

Artificial intelligence has played a potential role in present technological advancements. In terms of additive manufacturing or 3D printing techniques, computational AI models and algorithms such as artificial neural network, genetic algorithms, evolutionary algorithms, conventional machine learning techniques like decision tree, Naïve Bayes, K nearest neighbours, support vector machine, and ensemble methods including random forest, etc., has shown incredible results in the past few years. The applications of artificial intelligence in manufacturing are rapidly influencing most of the factors such as process optimization, material property prediction, determining the probability of product failure, real-time monitoring of processes, secure remote customer interactions, feature automation, material tuning, design feature recommendation, precise analysis, quality control/enhancement, or dynamic system modelling. Recent research in the field of VAT photopolymerization indicates that the creation of complex, versatile material systems with adaptable mechanical, chemical, and optical properties via the high-resolution processes includes a variety of 3D printing technologies, like stereolithography, digital illumination processing, and continuous liquid interface production. It has a compelling future in the last industrial revolution, Industry 4.0. This review compiles the evolution, current trends, open issues, and future computational AI models in 3D-printing VAT photopolymerization. Possibilities, prospects, and projects are well discussed to understand the significance of this technology.
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Metadaten
Titel
Computational AI models in VAT photopolymerization: a review, current trends, open issues, and future opportunities
verfasst von
Isha Sachdeva
Sivasubramani Ramesh
Utkarsh Chadha
Hruditha Punugoti
Senthil Kumaran Selvaraj
Publikationsdatum
17.08.2022
Verlag
Springer London
Erschienen in
Neural Computing and Applications / Ausgabe 20/2022
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-022-07694-4

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