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Manufacturing-induced stochastic constitutive behaviors of additive manufactured specimens: testing, data-driven modeling, and optimization.

Authors :
Chen, Baixi
Mao, Weining
Lin, Yangsheng
Ma, Wenqian
Hu, Nan
Source :
Rapid Prototyping Journal; 2024, Vol. 30 Issue 4, p662-676, 15p
Publication Year :
2024

Abstract

Purpose: Fused deposition modeling (FDM) is an extensively used additive manufacturing method with the capacity to build complex functional components. Due to the machinery and environmental factors during manufacturing, the FDM parts inevitably demonstrated uncertainty in properties and performance. This study aims to identify the stochastic constitutive behaviors of FDM-fabricated polylactic acid (PLA) tensile specimens induced by the manufacturing process. Design/methodology/approach: By conducting the tensile test, the effects of the printing machine selection and three major manufacturing parameters (i.e., printing speed S, nozzle temperature T and layer thickness t) on the stochastic constitutive behaviors were investigated. The influence of the loading rate was also explained. In addition, the data-driven models were established to quantify and optimize the uncertain mechanical behaviors of FDM-based tensile specimens under various printing parameters. Findings: As indicated by the results, the uncertain behaviors of the stiffness and strength of the PLA tensile specimens were dominated by the printing speed and nozzle temperature, respectively. The manufacturing-induced stochastic constitutive behaviors could be accurately captured by the developed data-driven model with the R<superscript>2</superscript> over 0.98 on the testing dataset. The optimal parameters obtained from the data-driven framework were T = 231.3595 °C, S = 40.3179 mm/min and t = 0.2343 mm, which were in good agreement with the experiments. Practical implications: The developed data-driven models can also be integrated into the design and characterization of parts fabricated by extrusion and other additive manufacturing technologies. Originality/value: Stochastic behaviors of additively manufactured products were revealed by considering extensive manufacturing factors. The data-driven models were proposed to facilitate the description and optimization of the FDM products and control their quality. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
13552546
Volume :
30
Issue :
4
Database :
Complementary Index
Journal :
Rapid Prototyping Journal
Publication Type :
Academic Journal
Accession number :
176927366
Full Text :
https://doi.org/10.1108/RPJ-09-2023-0334