This dataset was generated in the context of a comparative analysis of the performance of defect analysis methods in the paper: Additive manufacturing of multi-material parts – A tool for automated defect analysis.

Used software: MATLAB® R2024b, ImageJ (Version 1.54p 17 February 2025)

For both analyses the same images and parameters were used.

Used parameters:

- Resizing: None
- Scaling factor (Pixels per Milimeter): 840
- Preprocessing: Histogram Equalization (1%)
- Segmentation Threshold: 65

The analysis compared the results related to:

- Calculated Porosity
- Detected Defects
- Unassigned Material Area
- Unassigned Defect Area
- Number of Unassigned Defects

Comparison of the reference analysis using ImageJ (IMJ) and MultiPoroX (MPX)

References

Meyer, I., Glitt, L., Lachmayer, R. (2025). MultiPoroX: Automated multi-material porosity analysis tool [Data set]. LUIS. https://doi.org/10.25835/27xsmm9e

Meyer, I., Oel, M., Ehlers, T., & Lachmayer, R. (2023). Additive manufacturing of multi-material parts – Design guidelines for manufacturing of 316L/CuCrZr in laser powder bed fusion. Heliyon, 9(8), e18301. https://doi.org/10.1016/j.heliyon.2023.e18301

Acknowledgments

The project ”Additive Fertigung multimaterieller Komponenten zur nachhaltigen Energiewandlung” was funded by the European Regional Development Fund (ERDF) and the state of Lower Saxony – Project number ZW 7-87011865.

The project ”Major Research Instrumentation for integration of efficient effects in multi-material structural components” was funded by the Deutsche Forschungsgemeinschaft (DFG - German Research Foundation) - Project number 445707542.