Manufacturing-induced stochastic constitutive behaviors of additive manufactured specimens: testing, data-driven modeling, and optimization
ISSN: 1355-2546
Article publication date: 9 April 2024
Issue publication date: 1 May 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 R2 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.
Keywords
Acknowledgements
This work was financially supported by the National Natural Science Foundation of China (52008174) and Guangdong Provincial Key Laboratory of Modern Civil Engineering Technology (2021B1212040003). All the sources of support are gratefully acknowledged.
Declaration of competing interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Data availability: The data forming the basis of this study is available from the corresponding authors upon reasonable request.
Authorship contribution statement: Baixi Chen: Conceptualization, methodology, investigation, visualization, formal analysis, writing –original draft, writing – review and editing; Weining Mao: Conceptualization, methodology, investigation, visualization, data curation; Yangsheng Lin and Wenqian Ma: Methodology, investigation; Nan Hu: Conceptualization, methodology, supervision, funding acquisition, writing – review and editing.
Citation
Chen, B., Mao, W., Lin, Y., Ma, W. and Hu, N. (2024), "Manufacturing-induced stochastic constitutive behaviors of additive manufactured specimens: testing, data-driven modeling, and optimization", Rapid Prototyping Journal, Vol. 30 No. 4, pp. 662-676. https://doi.org/10.1108/RPJ-09-2023-0334
Publisher
:Emerald Publishing Limited
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