Advanced processing of 3D printed biocomposite materials using artificial intelligence. Issue 5 (4th April 2022)

• Record Type: Journal Article
• Authors: Verma, Deepak; Dong, Yu; Sharma, Mohit; Chaudhary, Arun Kumar
• Is Part Of: Materials and manufacturing processes. Volume 37:Issue 5(2022)
• Page Start: 518
• Page End: 538
• Publication Date: 2022-04-04
• Subjects: Additive manufacturing -- 3D printing; biocomposites; processing techniques; machine learning; deep learning; aerospace applications; biomedical applications; Manufacturing processes -- Periodicals; Materials -- Periodicals; Manufactured Materials; 670.5
• DOI: 10.1080/10426914.2021.1945090
• Languages: English
• ISSNs: 1042-6914

Abstract

ABSTRACT: Environmental implication is a key concern while utilizing the conventional synthetic polymers for composite applications. Biodegradable/biocompatible/natural polymeric materials can potentially resolve this issue by strategic replacement of traditional polymeric counterparts. Auxiliary to materials selection, the processing techniques has an essential role to influence the composite performance. Advanced additive manufacturing techniques have advantages over conventional polymer processing techniques due to their proficiency to print complex parts which can conform to intricate shape, minimize wastage, rapid prototyping and ease of product translation. Improved 3D printing such as powder based methods has been demonstrated to fabricate biocompatible parts like tooth implants. The current article includes the review on additive manufacturing techniques for the development of biocomposites, and further utilization of artificial intelligence (AI) in 3 D printing technologies. This review highlights how AI techniques such as machine learning and deep learning, supports efficiency and easy processibility of additive manufacturing methods for biocomposite development.