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Micromachines
Special Issues
Additive Manufacturing: Technology, Challenges and Applications
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Additive Manufacturing: Technology, Challenges and Applications

A special issue of Micromachines (ISSN 2072-666X). This special issue belongs to the section "D3: 3D Printing and Additive Manufacturing".

Deadline for manuscript submissions: closed (25 November 2022) | Viewed by 4073

Special Issue Editor

Dr. Santiago Ferrandiz

E-Mail Website
Guest Editor
Department of Mechanical Engineering and Materials, Universitat Politècnica de València (UPV), 03801 Alcoy, Spain
Interests: additive printing; injection; polymer and polymer composites; material characterization; FEM simulation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue focuses on recent advances in additive manufacturing processes, applications and technologies. There is a growing need to know determine the new industrial applications of AM, and identify the new materials that are being applied in the field. It is necessary to discover what the future trends of new technologies are. Each technology and each application sector present needs that must be considered, from the part’s design, to the processing conditions of the same. Original research papers and review articles are invited for this Special Issue.

Dr. Santiago Ferrandiz
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Micromachines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • additive manufacturing
  • AM trends
  • AM design
  • DFAM

Published Papers (2 papers)

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Research

17 pages, 4316 KiB  
Article
Knowledge-Based Design Algorithm for Support Reduction in Material Extrusion Additive Manufacturing
by Jaeseung Ahn, Jaehyeok Doh, Samyeon Kim and Sang-in Park
Micromachines 2022, 13(10), 1672; https://doi.org/10.3390/mi13101672 - 4 Oct 2022
Cited by 2 | Viewed by 1213
Abstract
Although additive manufacturing (AM) enables designers to develop products with a high degree of design freedom, the manufacturing constraints of AM restrict design freedom. One of the key manufacturing constraints is the use of support structures for overhang features, which are indispensable in [...] Read more.
Although additive manufacturing (AM) enables designers to develop products with a high degree of design freedom, the manufacturing constraints of AM restrict design freedom. One of the key manufacturing constraints is the use of support structures for overhang features, which are indispensable in AM processes, but increase material consumption, manufacturing costs, and build time. Therefore, controlling support structure generation is a significant issue in fabricating functional products directly using AM. The goal of this paper is to propose a knowledge-based design algorithm for reducing support structures whilst considering printability and as-printed quality. The proposed method consists of three steps: (1) AM ontology development, for characterizing a target AM process, (2) Surrogate model construction, for quantifying the impact of the AM parameters on as-printed quality, (3) Design and process modification, for reducing support structures and optimizing the AM parameters. The significance of the proposed method is to not only optimize process parameters, but to also control local geometric features for a better surface roughness and build time reduction. To validate the proposed algorithm, case studies with curve-based (1D), surface-based (2D), and volume (3D) models were carried out to prove the reduction of support generation and build time while maintaining surface quality. Full article
(This article belongs to the Special Issue Additive Manufacturing: Technology, Challenges and Applications)
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15 pages, 7414 KiB  
Article
Concurrent Topological Structure and Cross-Infill Angle Optimization for Material Extrusion Polymer Additive Manufacturing with Microstructure Modeling
by Ruixiao Tang, Chenghu Zhang and Jikai Liu
Micromachines 2022, 13(6), 852; https://doi.org/10.3390/mi13060852 - 29 May 2022
Cited by 1 | Viewed by 1608
Abstract
This paper contributes a concurrent topological structure and cross-infill angle optimization method for material extrusion type additive manufacturing (AM). This method features in modeling the process-induced material anisotropy through microscopic geometric modeling obtained by scanning electron micrographs. Numerical homogenization is performed to evaluate [...] Read more.
This paper contributes a concurrent topological structure and cross-infill angle optimization method for material extrusion type additive manufacturing (AM). This method features in modeling the process-induced material anisotropy through microscopic geometric modeling obtained by scanning electron micrographs. Numerical homogenization is performed to evaluate the equivalent effective properties of the 100-percentage cross-infilled local microstructures, and by introducing fitting functions, the relationship between equivalent effective material properties and varying cross-infill angles is empirically constructed. Then, optimization problems involving cross-infill angles as design variables are formulated, including concurrent optimization formulation. Numerical and experimental studies are conducted to illustrate the effectiveness of the proposed method. Both the numerical and experimental results demonstrate that the structural stiffness obtained by our proposed method has evidently improved. Full article
(This article belongs to the Special Issue Additive Manufacturing: Technology, Challenges and Applications)
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