Applications of Additive Manufacturing Technologies

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Advanced Manufacturing".

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1605

Special Issue Editors


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Guest Editor
Institute of Chemistry, Chinese Academy of Sciences, Beijing, China
Interests: 3D printing; dynamic polymers; soft robotics
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of Chemistry, Chinese Academy of Sciences, Beijing, China
Interests: self-assembly; functional coatings; dynamic polymers; 3D printing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Additive manufacturing (AM), also known as 3D printing, is an emerging rapid prototyping technology favored by many fields such as biomedicine, aerospace, and smart devices. Based on a computer-designed 3D model, additive manufacturing builds materials layer by layer through heating and melting, laser sintering, or light curing to create the desired solid 3D part. Compared to traditional processing methods, additive manufacturing eliminates the need for molds and cumbersome machining processes, and can be used to design and produce complex structures on demand that are difficult to achieve with traditional processing methods. A variety of additive manufacturing technologies have been developed, mainly including fused deposition molding (FDM), direct ink writing (DIW), stereolithography (SLA), digital light processing (DLP), and selective laser sintering (SLS). In addition, numerous printing materials have been developed, such as polymers, metals, and ceramics. These materials have many functions such as electrical and thermal conductivity, shape memory, self-healing, etc., and are widely employed in many such as bioengineering, sensors, and soft robotics.

This Special Issue aims to collect new insights regarding the application of additive manufacturing technologies in advanced fields such as sensors and robotics, focusing on modeling, material and structural design, fabrication, and control in practical applications.

Dr. Guangda Zhu
Dr. Yi Hou
Guest Editors

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Keywords

  • additive manufacturing
  • 3D printing
  • deposition molding (FDM)
  • direct ink writing (DIW)
  • stereolithography (SLA)
  • digital light processing (DLP)
  • selective laser sintering (SLS)

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Published Papers (1 paper)

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Research

21 pages, 5535 KiB  
Article
Generalized Design for Additive Manufacturing (DfAM) Expert System Using Compliance and Design Rules
by Bader Alwoimi Aljabali, Santosh Kumar Parupelli and Salil Desai
Machines 2025, 13(1), 29; https://doi.org/10.3390/machines13010029 - 6 Jan 2025
Viewed by 807
Abstract
Additive manufacturing (AM) has revolutionized the design and production of complex geometries by offering unprecedented creative freedom over traditional manufacturing. Despite its growing prominence, AM lacks automated and standardized design rules tailored to specific AM processes, resulting in time-consuming and expert-dependent manual verification. [...] Read more.
Additive manufacturing (AM) has revolutionized the design and production of complex geometries by offering unprecedented creative freedom over traditional manufacturing. Despite its growing prominence, AM lacks automated and standardized design rules tailored to specific AM processes, resulting in time-consuming and expert-dependent manual verification. To address these limitations, this research introduces a novel design for additive manufacturing (DfAM) framework consisting of two complementary models designed to automate the design process. The first model, based on a decision tree algorithm, evaluates part compliance with established AM design rules. A modified J48 classifier was implemented to enhance data mining accuracy by achieving a 91.25% classification performance accuracy. This model systematically assesses whether input part characteristics meet AM processing standards, thereby providing a robust tool for verifying design rules. The second model features an AM design rule engine developed with a Python-based graphical user interface (GUI). This engine generates specific recommendations for design adjustments based on part characteristics and machine compatibility, offering a user-friendly approach for identifying potential design issues and ensuring DfAM compliance. By linking part specifications to various AM techniques, this model supports both researchers and engineers in anticipating and mitigating design flaws. Overall, this research establishes a foundation for a comprehensive DfAM expert system. Full article
(This article belongs to the Special Issue Applications of Additive Manufacturing Technologies)
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