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Parameter Optimization for 3D Printing of Continuous Carbon Fiber/Epoxy Composites

INTAMSYS industrial 3d printing

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In the recently published ‘A Sensitivity Analysis-Based Parameter Optimization Framework for 3D Printing of Continuous Carbon Fiber/Epoxy Composites,’ researchers continue to explore the world of enhanced materials for fabrication of prototypes and functional components. Focusing on improving continuous carbon fiber/epoxy composites (CCF/EPCs), the researchers performed a sensitivity analysis for optimizing parameters, as well as 3D printing and evaluating samples.

Today, fiber-reinforced polymer composites (FRPCs) are used in critical applications like construction, transportation, and aerospace, attractive due to qualities like:

  • Low density
  • High strength
  • Outstanding designability
  • Modulus

While traditional methods may be more time-consuming and expensive, 3D printing offers a host of benefits—from higher speeds in manufacturing to the elimination of molds, affordability, the potential for greater innovation, lightweight (yet stronger) products, and more. In relation to FRPCs, scientists and manufacturers have made huge strides with a range of materials, to include continuous fibers. More so, however, they have made strides in understanding the effects of even the slightest changes in printing parameters like speed, temperatures, and pressure.

“A slight variation may cause a significant change in the final mechanical properties,” stated the researchers. “Although the experimental method would be a preferred and reliable way to acquire the optimal parameters, it is practically difficult or even impossible to carry out sufficient experiments because it would be a time-consuming and unaffordable process. Sensitivity analysis (SA) evaluates how the variations in the model output can be apportioned to variations in model inputs.

“In addition to being used in biology and chemistry, SA has also been applied in engineering and environmental science.”

The outline of the proposed framework.

The 3D printing process for continuous carbon fiber/epoxy composites (CCF/EPCs).

For this study, the researchers analyzed experimental data, along with creating a surrogate model for process parameters. SA was used to calculate parameters and mechanical properties, followed by further testing to verify the SA-based framework. And while 3D printing CCF/EPCs may be easy, the researchers found that controlling parameters is another matter. Parameters such as printing speed, thickness, and space are ‘critical,’ but challenging to manipulate.

The 3D printing process parameters.

Three experiments were conducted to confirm results, regarding flexural strength and flexural modulus, resulting in averages of 912.1 MPa and 69.28 GPa.

“ … the results showed that the sensitivity analysis-based optimization framework can serve as a high-accuracy tool to optimize the 3D printing parameters for the additive manufacturing of CCF/EPCs and to predict the flexural strength and flexural modulus of the printed samples.

“While multivariate sensitivity analysis techniques can identify the important parameters for all the mechanical properties considered based on the SVR model of each property, the multi-objective optimization method can search the important parameters which optimize all the mechanical properties simultaneously. Further detailed research for multiple properties will be conducted in future work.”

The flexural strength and flexural modulus of the printed CCF/EPCs samples under the optimal parameters.

As users continue to transform software, hardware, and materials for specific project requirements, a wide range of composites is becoming available—from conductive silver to antioxidant PLA, wood composites, glass composites, and more.

What do you think of this news? Let us know your thoughts! Join the discussion of this and other 3D printing topics at 3DPrintBoard.com.

[Source / Images: ‘A Sensitivity Analysis-Based Parameter Optimization Framework for 3D Printing of Continuous Carbon Fiber/Epoxy Composites’]

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