Abstract
This paper describes the collection of a large dataset (6930 measurements) on dimensional error in the fused deposition modeling (FDM) additive manufacturing process for full-density parts. Three different print orientations were studied, as well as seven raster angles ( 0 ∘ , 15 ∘ , 30 ∘ , 45 ∘ , 60 ∘ , 75 ∘ , and 90 ∘ ) for the rectilinear infill pattern. All measurements were replicated ten times on ten different samples to ensure a comprehensive dataset. Eleven polymer materials were considered: acrylonitrile butadiene styrene (ABS), polylactic acid (PLA), high-temperature PLA, wood-composite PLA, carbon-fiber-composite PLA, copper-composite PLA, aluminum-composite PLA, high-impact polystyrene (HIPS), polyethylene terephthalate glycol-enhanced (PETG), polycarbonate, and synthetic polyamide (nylon). The samples were ASTM-standard impact-testing samples, since this geometry allows the measurement of error on three different scales; the nominal dimensions were 3.25 mm thick, 63.5 mm long, and 12.7 mm wide. This dataset is intended to give engineers and product designers a basis for judging the accuracy and repeatability of the FDM process for use in manufacturing of end-user products.
Highlights
The sustainability of manufacturing processes has been a topic of much discussion in recent years, especially with the rise of “mass customization” culture
To further study the aspects of fused deposition modeling (FDM) dimensional accuracy and repeatability, a large dataset of observed dimensional errors for various materials and printing parameters was collected using a large number of relatively simple identical parts; the summary, major considerations, and the collection procedure are discussed in the proceeding sections
This section gives the results for High-Temperature PLA (HTPLA) in terms of three deliverables: a color image showing the 21 samples for one replication of the experiment (Figure 8), a set of plots showing |δ| and mean percent error (MPE) for each of the dimensional measurements (Figure 9), and a table summarizing the statistical measures described previously (Table 4)
Summary
The sustainability of manufacturing processes has been a topic of much discussion in recent years, especially with the rise of “mass customization” culture. To further study the aspects of FDM dimensional accuracy and repeatability, a large dataset of observed dimensional errors for various materials and printing parameters was collected using a large number of relatively simple identical parts; the summary, major considerations, and the collection procedure are discussed in the proceeding sections. This dataset is intended to assist designers and process engineers in evaluating the feasibility of FDM as an end-product manufacturing process. This data will be useful as a training input for finite element analyses, for optimization algorithms, and for machining learning processes that evaluate FDM
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