DOAJ Open Access 2023

Machine Learning-Based Investigation of the 3D Printer Cooling Effect on Print Quality in Fused Filament Fabrication: A Cybersecurity Perspective

Haijun Si Zhicheng Zhang Orkhan Huseynov Ismail Fidan Syed Rafay Hasan +1 lainnya

Abstrak

Additive manufacturing (AM), also known as three-dimensional (3D) printing, is the process of building a solid object in a layer-wise manner. Cybersecurity is a prevalent issue that appears more and more frequently as AM becomes popular. This paper focuses on the effect of fan speed on the printing quality and presents a plugin called Fan Speed Attack Detection (FSAD) that predicts and monitors fan speeds throughout the printing process. The goal of the plugin is to prevent cybersecurity attacks, specifically targeting fan speed. Using the proposed FSAD, any fan speed changes during the printing process are evaluated to see whether the printer can sustain the abnormal fan speed change and still maintain good print quality.

Topik & Kata Kunci

Engineering machinery, tools, and implements Technological innovations. Automation

Penulis (6)

Haijun Si

Zhicheng Zhang

Orkhan Huseynov

Ismail Fidan

Syed Rafay Hasan

Mohamed Mahmoud

Format Sitasi

APA MLA BibTeX

Si, H., Zhang, Z., Huseynov, O., Fidan, I., Hasan, S.R., Mahmoud, M. (2023). Machine Learning-Based Investigation of the 3D Printer Cooling Effect on Print Quality in Fused Filament Fabrication: A Cybersecurity Perspective. https://doi.org/10.3390/inventions8010024

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Informasi Jurnal

Tahun Terbit: 2023
Sumber Database: DOAJ
DOI: 10.3390/inventions8010024
Akses: Open Access ✓