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Applied Sciences
Special Issues
New Insights into Additive Manufacturing of Intelligent Materials
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New Insights into Additive Manufacturing of Intelligent Materials

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Industrial Technologies".

Deadline for manuscript submissions: 30 December 2024 | Viewed by 1257

Special Issue Editor

Dr. Marcelo Garcia

E-Mail Website
Guest Editor
Faculty of Systems, Electronics and Industrial Engineering, Universidad Tecnica de Ambato (UTA), Ambato 180206, Ecuador
Interests: IEC-61499; robotics; IoT; CPPS; automation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This scholarly exploration seeks to elucidate the intricate interplay between additive manufacturing, intelligent materials, and artificial intelligence (AI) technologies. Contributions to this issue are invited to scrutinize the development of responsive smart materials, employing sophisticated sensors and actuators, as well as pioneering applications of multi-material printing techniques. Furthermore, research endeavors are encouraged to harness AI algorithms for the optimization of design, thereby augmenting the efficiency and precision of additive manufacturing processes.

The confluence of AI with additive manufacturing has demonstrated a propensity to enhance product quality, instigate innovation, bolster productivity, and amplify profitability. This integration has manifested in the creation of intricate geometries, refinement of material properties, and mitigation of production time and costs. The present Special Issue functions as a scholarly forum for the exchange of insights, innovations, and experimental findings, thereby cultivating a nuanced comprehension of the intricate nexus between additive manufacturing, intelligent materials, and artificial intelligence. The spectrum of research interests spans the gamut, encompassing the development of stimuli-responsive smart materials, the integration of advanced sensors and actuators, and the inventive application of multi-material printing techniques.

The transformative potential of AI integration with additive manufacturing is poised to revolutionize the manufacturing industry. Accordingly, this Special Issue endeavors to furnish novel insights into this evolving landscape. Researchers and practitioners are invited to contribute to this intellectual discourse, thereby advancing the collective knowledge and understanding of the domain of additive manufacturing of intelligent materials.

Dr. Marcelo V. Garcia
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. Applied Sciences is an international peer-reviewed open access semimonthly 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 2400 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
  • intelligent materials
  • artificial intelligence
  • 3D printing
  • smart sensors
  • actuator integration
  • multi-material printing
  • design optimization
  • advanced manufacturing
  • functional materials
  • computational tools
  • smart structures
  • additive fabrication
  • material science
  • emerging technologies
  • Industry 4.0

Published Papers (1 paper)

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Research

19 pages, 3296 KiB  
Article
Immersive Digital Twin under ISO 23247 Applied to Flexible Manufacturing Processes
by Gustavo Caiza and Ricardo Sanz
Appl. Sci. 2024, 14(10), 4204; https://doi.org/10.3390/app14104204 - 15 May 2024
Viewed by 1011
Abstract
Digital twin (DT) technology provides a path for implementing cyber–physical systems (CPS) and developing smart manufacturing because they are essential tools for monitoring and controlling manufacturing processes. It is considered a vital technology in smart manufacturing and is being widely researched in academia [...] Read more.
Digital twin (DT) technology provides a path for implementing cyber–physical systems (CPS) and developing smart manufacturing because they are essential tools for monitoring and controlling manufacturing processes. It is considered a vital technology in smart manufacturing and is being widely researched in academia and industry. Furthermore, the combination of DTs and immersive environments has shown great potential for integrating novel capabilities into the new generation of CPS. This research presents an architecture for implementing immersive digital twins under ISO 23247 in flexible manufacturing processes. The proposed system is based on the integration of DT technologies in conjunction with augmented reality (AR) and gesture tracking, and validation was performed in the sorting station of the MPS 500 to increase the interaction and flexibility between physical and virtual environments in real time, thus enhancing the capabilities of the DT. The methodology used for the design and implementation of the DT includes (1) general principles and requirements; (2) models with functional views based on domains and entities; (3) attributes of the observable manufacturing elements; and (4) protocols for the exchange of information between entities. The results show that the integration of these technologies improves the monitoring, control, and simulation capabilities of processes using 3D resources and immersive environments, achieving a higher level of interactivity. In addition, error detection tests were carried out, where a reduction of time was observed in the resolution of errors that may be caused by internal or external disturbances of the process, thus avoiding production delays. Full article
(This article belongs to the Special Issue New Insights into Additive Manufacturing of Intelligent Materials)
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