Emerging Applications of Machine Learning in 3D Printing
Source abstract
Abstract
Three-dimensional (3D) printing techniques already enable the precise deposition of many materials, becoming a promising approach for materials engineering, mechanical engineering, or biomedical engineering. Recent advances in 3D printing enable scientists and engineers to create models with precisely controlled and complex microarchitecture, shapes, and surface finishes, including multi-material printing. The incorporation of artificial intelligence (AI) at various stages of 3D printing has made it possible to reconstruct objects from images (including, for example, medical images), select and optimize materials and the printing process, and monitor the lifecycle of products. New emerging opportunities are provided by the ability of machine learning (ML) to analyze complex data sets and learn from previous (historical) experience and predictions to dynamically optimize and individuate products and processes. This includes the synergistic capabilities of 3D printing and ML for the development of personalized products.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Additive Manufacturing and 3D Printing Technologies · 3D Printing in Biomedical Research · Additive Manufacturing Materials and Processes
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Computer Science, Kazimierz Wielki University, Chodkiewicza 30, 85-064 Bydgoszcz, Poland
Faculty of Mechatronics, Kazimierz Wielki University, Chodkiewicza 30, 85-064 Bydgoszcz, Poland
Funding
Kazimierz Wielki University
References (85)
Show source-provided references
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