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牙科领域中使用熔丝制造技术增材制造聚乳酸面临的挑战与未来展望

Challenges and Future Perspectives for Additively Manufactured Polylactic Acid Using Fused Filament Fabrication in Dentistry.

作者信息

Kharmanda Ghais

机构信息

Mechanics Laboratory of Normandy, INSA Rouen, 76800 St Etienne du Rouvray, France.

3D printing 4U (UG), Nördlinger Str. 10, 51103 Cologne, Germany.

出版信息

J Funct Biomater. 2023 Jun 22;14(7):334. doi: 10.3390/jfb14070334.

Abstract

Additive manufacturing (AM), which is also called rapid prototyping/3D printing/layered manufacturing, can be considered as a rapid conversion between digital and physical models. One of the most used materials in AM is polylactic acid (PLA), which has advantageous material properties such as biocompatibility, biodegradability, and nontoxicity. For many medical applications, it is considered as a leading biomaterial. In dentistry, in addition to its uses in dental models (education, teaching, simulation needs), it can be used for therapeutic objectives and tissue engineering. The fused filament fabrication (FFF) technique, also called fused deposition modeling (FDM), is widely used as an AM technique to perform complex and functional geometries directly from CAD files. In this review, the objective was to present the different challenges and future perspectives of this additively manufactured material by using FFF in dentistry areas. Some suggestions for future directions to extend to more dental applications (support structures, lattice structures, etc.) and to consider more criteria (sustainability, uncertainty etc.) will be discussed. Advanced studies such as machine learning (ML) techniques will be suggested to reduce the failure cases when using the additively manufactured PLA by FFF in dentistry.

摘要

增材制造(AM),也被称为快速成型/3D打印/分层制造,可被视为数字模型与物理模型之间的快速转换。增材制造中最常用的材料之一是聚乳酸(PLA),它具有生物相容性、生物可降解性和无毒等有利的材料特性。在许多医学应用中,它被视为一种领先的生物材料。在牙科领域,除了用于牙科模型(教育、教学、模拟需求)外,它还可用于治疗目的和组织工程。熔融长丝制造(FFF)技术,也称为熔融沉积建模(FDM),被广泛用作一种增材制造技术,可直接从CAD文件制作复杂的功能几何形状。在这篇综述中,目的是介绍在牙科领域使用FFF对这种增材制造材料所面临的不同挑战和未来前景。将讨论未来扩展到更多牙科应用(支撑结构、晶格结构等)以及考虑更多标准(可持续性、不确定性等)的方向建议。还将提出诸如机器学习(ML)技术等高级研究,以减少在牙科领域通过FFF使用增材制造的PLA时的失败案例。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5102/10381451/244b09202e4e/jfb-14-00334-g001.jpg

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