Six-DOF Additive Manufacturing Device Experimental Parameters and Results

Experimental data from Xingguo Han's 2026 research on an adaptive hierarchical slicing algorithm for fused deposition additive manufacturing. The dataset contains parameters and roughness measurements from models printed on a six-degree-of-freedom AM device. It compares the performance of equal thickness, normal vector-based, and the proposed contour-based slicing algorithms.

Use Cases

• Compare surface roughness outcomes from equal thickness, normal vector-based, and contour-based slicing algorithms for different model types.
• Analyze the relationship between model part classification (non-significant, general, complex feature) and the chosen slicing criterion (normal vector angle, adjacent patch angle, Taubin index).
• Correlate geometric characteristics of STL models, such as contour intersection point number, with resulting printing accuracy and efficiency metrics.
• Validate the proposed adaptive hierarchical algorithm's performance on specific test models like the ship, vase, and dice using roughness meter data.

Strengths

• Direct experimental results from a six-DOF AM device, providing real-world validation data.
• Compares three distinct slicing algorithms (equal thickness, normal vector-based, proposed method) on multiple models.
• Includes quantitative surface roughness measurements from a roughness meter.

Limitations

• Dataset is very small at 5.5 KB, indicating a limited number of experimental runs or parameters.
• Specific row count, column names, and sample data are unavailable, limiting initial assessment of structure.
• Geographic and organizational context for the experiments is not provided.

Provenance

Source

Xingguo Han via figshare.

Collection Method

Experimental data from printing and testing models (ship, vase, dice) on a six-DOF additive manufacturing device.

Freshness

Last updated in 2026, indicating it is a forward-dated or planned dataset.