Cargando…
Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance
In recent years, there has been a growing interest in the field of 3D printing technology. Among the various technologies available, fused deposition modeling (FDM) has emerged as the most popular and widely used method. However, achieving optimal results with FDM presents a significant challenge du...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10459717/ https://www.ncbi.nlm.nih.gov/pubmed/37631476 http://dx.doi.org/10.3390/polym15163419 |
_version_ | 1785097478897401856 |
---|---|
author | Portoacă, Alexandra Ileana Ripeanu, Razvan George Diniță, Alin Tănase, Maria |
author_facet | Portoacă, Alexandra Ileana Ripeanu, Razvan George Diniță, Alin Tănase, Maria |
author_sort | Portoacă, Alexandra Ileana |
collection | PubMed |
description | In recent years, there has been a growing interest in the field of 3D printing technology. Among the various technologies available, fused deposition modeling (FDM) has emerged as the most popular and widely used method. However, achieving optimal results with FDM presents a significant challenge due to the selection of appropriate process parameters. Therefore, the objective of this research was to investigate the impact of process parameters on the tribological and frictional behavior of acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) 3D-printed parts. The design of experiments (DOE) technique was used considering the input design parameters (infill percentage and layer thickness) as variables. The friction coefficient values and the wear were determined by experimental testing of the polymers on a universal tribometer employing plane friction coupling. Multi-response optimization methodology and analysis of variance (ANOVA) were used to highlight the dependency between the coefficient of friction, surface roughness parameters, and wear on the process parameters. The optimization analysis revealed that the optimal 3D printing input parameters for achieving the minimum coefficient of friction and linear wear were found to be an infill percentage of 50% and layer thickness of 0.1 mm (for ABS material), and an infill percentage of 50%, layer thickness of 0.15 mm (for PLA material). The suggested optimization methodology (which involves minimizing the coefficient of friction and cumulative linear wear) through the optimized parameter obtained provides the opportunity to select the most favorable design conditions contributing to a more sustainable approach to manufacturing by reducing overall material consumption. |
format | Online Article Text |
id | pubmed-10459717 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-104597172023-08-27 Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance Portoacă, Alexandra Ileana Ripeanu, Razvan George Diniță, Alin Tănase, Maria Polymers (Basel) Article In recent years, there has been a growing interest in the field of 3D printing technology. Among the various technologies available, fused deposition modeling (FDM) has emerged as the most popular and widely used method. However, achieving optimal results with FDM presents a significant challenge due to the selection of appropriate process parameters. Therefore, the objective of this research was to investigate the impact of process parameters on the tribological and frictional behavior of acrylonitrile butadiene styrene (ABS) and polylactic acid (PLA) 3D-printed parts. The design of experiments (DOE) technique was used considering the input design parameters (infill percentage and layer thickness) as variables. The friction coefficient values and the wear were determined by experimental testing of the polymers on a universal tribometer employing plane friction coupling. Multi-response optimization methodology and analysis of variance (ANOVA) were used to highlight the dependency between the coefficient of friction, surface roughness parameters, and wear on the process parameters. The optimization analysis revealed that the optimal 3D printing input parameters for achieving the minimum coefficient of friction and linear wear were found to be an infill percentage of 50% and layer thickness of 0.1 mm (for ABS material), and an infill percentage of 50%, layer thickness of 0.15 mm (for PLA material). The suggested optimization methodology (which involves minimizing the coefficient of friction and cumulative linear wear) through the optimized parameter obtained provides the opportunity to select the most favorable design conditions contributing to a more sustainable approach to manufacturing by reducing overall material consumption. MDPI 2023-08-16 /pmc/articles/PMC10459717/ /pubmed/37631476 http://dx.doi.org/10.3390/polym15163419 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Portoacă, Alexandra Ileana Ripeanu, Razvan George Diniță, Alin Tănase, Maria Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance |
title | Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance |
title_full | Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance |
title_fullStr | Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance |
title_full_unstemmed | Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance |
title_short | Optimization of 3D Printing Parameters for Enhanced Surface Quality and Wear Resistance |
title_sort | optimization of 3d printing parameters for enhanced surface quality and wear resistance |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10459717/ https://www.ncbi.nlm.nih.gov/pubmed/37631476 http://dx.doi.org/10.3390/polym15163419 |
work_keys_str_mv | AT portoacaalexandraileana optimizationof3dprintingparametersforenhancedsurfacequalityandwearresistance AT ripeanurazvangeorge optimizationof3dprintingparametersforenhancedsurfacequalityandwearresistance AT dinitaalin optimizationof3dprintingparametersforenhancedsurfacequalityandwearresistance AT tanasemaria optimizationof3dprintingparametersforenhancedsurfacequalityandwearresistance |