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Surface Roughness Prediction in Fused Deposition Modeling: An Engineered Model

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Design Tools and Methods in Industrial Engineering III (ADM 2023)

Abstract

Additive manufacturing (AM) allows to create complex shapes and to improve the performance of critical components in different fields. The characteristics of the as-built parts can be an obstacle in terms of satisfaction of the parts’ quality requirements. Concerning the manufacturing process, the relationship among the process parameters, microstructure and mechanical properties is crucial in different areas and involves innovative and traditional fabrication techniques. Fused Deposition Modeling (FDM) is widely employed to fabricate devices with tailored and enhanced properties.

In this context, the process parameters clearly influence the quality of devices fabricated from different polymer-based materials, according to the specific AM technology. As reported in the literature, many theoretical models for the prediction of the surface quality focus on the concept of roughness. Furthermore, several parameters have also been proposed to assess the surface quality.

Benefiting from advances in design strategies and methodologies of analysis, the aim of the current research was to provide further insight into the development of models for surface roughness prediction in FDM.

The relationship among the layer height, printing speed, flow rate and extrusion width was considered and implemented in the model. Preliminary experimental analyses were also performed.

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Correspondence to Chiara de Crescenzo .

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de Crescenzo, C. et al. (2024). Surface Roughness Prediction in Fused Deposition Modeling: An Engineered Model. In: Carfagni, M., Furferi, R., Di Stefano, P., Governi, L., Gherardini, F. (eds) Design Tools and Methods in Industrial Engineering III. ADM 2023. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-031-52075-4_13

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  • DOI: https://doi.org/10.1007/978-3-031-52075-4_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-52074-7

  • Online ISBN: 978-3-031-52075-4

  • eBook Packages: EngineeringEngineering (R0)

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