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3D modeling technology, as well as additive manufacturing, has changed the processes of industries, allowing the creation and production of complex and unique prototypes with increased speed and versatility. However, the effectiveness of additive manufacturing is primarily based on the capabilities of the 3D design software used to create these objects. The state of 3D modeling software in additive manufacturing currently has both advantages and disadvantages: existing tools have basic design support functionality, but they often lack the ability to optimize designs for increased efficiency and productivity. This inspires research into how to incorporate artificial intelligence into 3D modeling software to solve these problems and improve the additive manufacturing process. Using artificial intelligence techniques such as machine learning and generative design, the accuracy and efficiency of 3D models can be significantly improved, leading to improved manufacturing efficiency. However, integrating artificial intelligence into existing 3D modeling software faces challenges related to compatibility, data management, and user acceptance. With a discussion of this topic and a show demonstrating the successful implementation of AI in 3D modeling for additive manufacturing, the impact of AI-enhanced software on the industry is clear. This article aims to explore the current state of 3D modeling software in relation to additive manufacturing, discuss how AI can be used for optimization, and assess the implications and possible future steps of integrating AI into 3D modeling to improve efficiency in relation to additive manufacturing. production.
Тарасов et al. (Tue,) studied this question.