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

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, Naive 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.

Automated summary

Artificial intelligence has shown great potential in the field of 3D printing, contributing to process optimization, material property prediction, real-time monitoring, quality control, and more. VAT photopolymerization technology has demonstrated the capability to create complex material systems with adaptable properties, playing a significant role in Industry 4.0. This review summarizes the evolution, current trends, challenges, and future AI models in 3D-printing VAT photopolymerization, providing insights into the significance of this technology.