Regression Model for Optimization and Prediction of Tensile Strength of a PLA Prototype Printed

The experimental studies on prototypes printed in 3D with polylactic acid (PLA) material still seek to characterize the mechanical behavior and the deformations of these printed samples according to the various solicitations. The huge number of parameters intervening in these properties makes the co...

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Vydáno v:Journal of advanced computational intelligence and intelligent informatics Ročník 26; číslo 6; s. 952 - 958
Hlavní autoři: Hamouti, Lahcen, Farissi, Omar El, Outemssa, Omar
Médium: Journal Article
Jazyk:angličtina
Vydáno: Tokyo Fuji Technology Press Co. Ltd 20.11.2022
Témata:
3-D printers
Additive manufacturing
Artificial intelligence
Informatics
Mechanical properties
Medical research
Neural networks
Optimization
Parameters
Polylactic acid
Process controls
Prototypes
Regression models
Tensile strength
Three dimensional printing
ISSN:1343-0130, 1883-8014
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Shrnutí:The experimental studies on prototypes printed in 3D with polylactic acid (PLA) material still seek to characterize the mechanical behavior and the deformations of these printed samples according to the various solicitations. The huge number of parameters intervening in these properties makes the control of process difficult and expensive. Previous studies on the impact of these parameters on the mechanical properties are limited to the investigation of a very less number of parameters. The objective of the present study is to take advantage of artificial intelligence tools, and to exploit the experimental results, in order to present artificial models that are able to optimize the choice of parameters intervening in the properties (tensile strength) of printed parts.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1343-0130
1883-8014
DOI:10.20965/jaciii.2022.p0952