Application of RSM Method in Optimization of 3D Printing Machine Process Parameters Using Biocomposite Materials (PMMA/Hydroxyapatite) to Get the Highest Tension Strength

Authors

  • Angger Bagus Prasetiyo Institut Teknologi Nasional Yogyakarta
  • Kartinasari Ayuhikmatin Sekarjati Institut Sains dan Teknologi AKPRIND Yogyakarta
  • Alva Edy Tontowi Universitas Gadjah Mada

DOI:

https://doi.org/10.22219/jemmme.v6i2.17780

Keywords:

RSM, tensile strength, PMMA

Abstract

Solution developed to improve the structure of human bone in synthetic bone. Composites manufactured from polymethylmetacrylate are frequently employed in the medical field (PMMAPure PMMA, on the other hand, has restricted mechanical qualities, as well as being less compatible, rigid, and non-bioactive. This research will mix PMMA material with hydroxyapatite (HA) material. The material's composition is PMMA: MMA = 1: 1, with a hydroxyapatite (HA) to PMMA powder ratio of 0.50: 1 (w/w). The material will be printed through a 3D Printing machine which has a 1.5 mm nozzle. This 3D Printing machine undergoes periodic development, but the results obtained are not in accordance with the needs, especially the tensile strength of the specimen. Therefore, it is necessary to conduct research to determine the ability of the 3D Printing machine printing process by optimizing the parameters of the 3D Printing machine. Experimental results and analysis using the RSM method show the machining parameters of the 3D printing machine on PMMA/HA material to get the highest optimal tensile strength at the point of 13,670 mm/s for the perimeter speed parameter, 76,330 mm/s for the infill speed parameter and 33,670% point for the fill density

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References

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Published

2021-12-17

How to Cite

Bagus Prasetiyo, A., Sekarjati, K. A. ., & Tontowi, A. E. (2021). Application of RSM Method in Optimization of 3D Printing Machine Process Parameters Using Biocomposite Materials (PMMA/Hydroxyapatite) to Get the Highest Tension Strength. Journal of Energy, Mechanical, Material, and Manufacturing Engineering, 6(2), 119–126. https://doi.org/10.22219/jemmme.v6i2.17780

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