ArticlePolymers2020
On the Heuristic Procedure to Determine Processing Parameters in Additive Manufacturing Based on Materials Extrusion.
Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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10 citing papers in PubMed.
- High-Performance Polymer Blends: Manufacturing of Polyetherimide (PEI)-Polycarbonate (PC)-Based Filaments for 3D Printing.Polymers · 2024Article
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- 3D-Printed Fiber-Reinforced Polymer Composites by Fused Deposition Modelling (FDM): Fiber Length and Fiber Implementation Techniques.Polymers · 2022Review
- Effective Stiffness of Fused Deposition Modeling Infill Lattice Patterns Made of PLA-Wood Material.Polymers · 2022Article
- Comparison between Tests and Simulations Regarding Bending Resistance of 3D Printed PLA Structures.Polymers · 2021Article
- The Dynamic Impact Response of 3D-Printed Polymeric Sandwich Structures with Lattice Cores: Numerical and Experimental Investigation.Polymers · 2021Article
- Article
- Mechanical Properties of Flexible TPU-Based 3D Printed Lattice Structures: Role of Lattice Cut Direction and Architecture.Polymers · 2021Article
- Effect of Printing Parameters on the Thermal and Mechanical Properties of 3D-Printed PLA and PETG, Using Fused Deposition Modeling.Polymers · 2021Article
- Numerical Simulation of a Core-Shell Polymer Strand in Material Extrusion Additive Manufacturing.Polymers · 2021Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We present a heuristic procedure for determining key processing parameters (PPs) in materials-extrusion-based additive manufacturing processes. The concept relies on a design-of-experiment approach and consists of eleven "test objects" to determine the optimal combinations of key PPs values, starting with the PPs for printing the first layer and progressing to more complex geometric features, e.g., "bridges". In each of the test objects, several combinations of the known PPs' values are used, and only the values resulting in the best printed-part quality are selected for the following tests. The concept is intrinsically insensitive to different artefacts of the additive manufacturing machine (e.g., discrepancies between the nominal and actual nozzle diameters, and improper calibration of the feeding screws) and the optimal values of key PPs for manufacturing defect-free parts under the actual processing conditions can be determined. We validated the proposed procedure for two common commercial polymer feedstock materials, and we show that, by using the proposed procedure, it is possible to reduce the optimization time down to several hours, as well as to reduce the amount of consumed feedstock material. Tensile tests revealed a strong effect of amorphous and semi-crystalline nature of the polymer on the results of optimization. To the best of our knowledge, this is the first attempt to describe a systematic approach for optimizing PPs for materials extrusion-based additive manufacturing processes without relying on statistical data analysis or virtual simulations. The concept was implemented as a web-tool 3DOptimizer
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