Experimental Results of FDM Slicing Algorithms on Ship and Vase Models

Experimental results compare three slicing algorithms for Fused Deposition Modeling on ship, vase, and dice models. The dataset contains measured surface roughness data from prints produced by a six-degree-of-freedom additive manufacturing device. Xingguo Han published this data on figshare in April 2026.

Use Cases

• Compare surface roughness results from equal-thickness, normal vector-based, and contour-based adaptive slicing algorithms.
• Analyze the relationship between model part classification (non-significant, general, complex features) and resulting print quality metrics.
• Validate the performance of the proposed adaptive hierarchical algorithm against established methods using specific test models (ship, vase, dice).

Strengths

• Data is derived from controlled physical experiments using a six-DOF AM device and a roughness meter.
• Results directly compare three distinct algorithmic approaches on multiple 3D models.
• Published under a permissive CC-BY-4.0 license for reuse.

Limitations

• Dataset is very small at 5.5 KB, indicating limited experimental runs or metrics.
• Specific sample size, number of measurements, and raw columnar data are unknown.
• The future publication date (2026-04-08) suggests the data may be a placeholder or pre-release.

Provenance

Source

figshare, authored by Xingguo Han.

Collection Method

Experimental results from 3D printing tests using a specific six-degree-of-freedom additive manufacturing device.

Freshness

Last updated date is listed as 2026-04-08, which is in the future relative to the current date.