RDM-3D: A Remote Dashboard for 3D Printer Performance Monitoring

  • Osama T. Alshaheen*
  • , Zeashan H. Khan
  • , Samir N. Mekid
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This research project focuses on the development and implementation of a digital twin system aimed at addressing limitations inherent in 3D printing technology. Leveraging IoT sensors and predictive maintenance algorithms, the project endeavors to enable remote monitoring and proactive identification of potential failures during the printing process. The digital twin, synchronized with the physical 3D printer, aims to replicate real-time operational dynamics while facilitating predictive maintenance based on sensor data analysis. The integration of Node-RED for the dashboard interface, alongside comprehensive sensor integration and testing phases, forms the core of this research. The ultimate goal is to enhance operational efficiency, minimize downtime, and optimize 3D printing processes by leveraging advanced digital twin capabilities integrated with IoT sensor technologies.

Original languageEnglish
Title of host publication1st International Conference on Innovative Engineering Sciences and Technological Research, ICIESTR 2024 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350348637
DOIs
StatePublished - 2024
Event1st International Conference on Innovative Engineering Sciences and Technological Research, ICIESTR 2024 - Muscat, Oman
Duration: 14 May 202415 May 2024

Publication series

Name1st International Conference on Innovative Engineering Sciences and Technological Research, ICIESTR 2024 - Proceedings

Conference

Conference1st International Conference on Innovative Engineering Sciences and Technological Research, ICIESTR 2024
Country/TerritoryOman
CityMuscat
Period14/05/2415/05/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • 3D printer
  • IoT
  • condition monitoring
  • digital twin

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Aerospace Engineering
  • Civil and Structural Engineering
  • Safety, Risk, Reliability and Quality
  • Computational Mathematics
  • Control and Optimization

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