Context and methodology
This dataset was developed within the field of Additive Manufacturing (AM), specifically focusing on Multi-Material Stereo Lithography (MMSL). It investigates the mechanical behavior of heterogeneous cellular structures fabricated using a modified MMSL platform. The dataset provides the experimental base for how different topologies and material distributions influence mechanical properties. The dataset was created through the following workflow:
Design: 60 unique combinations where considered in the design space, 20 of them have been selected for the following training steps, 4 for the validation. The selection methodology is part of this dataset.
Fabrication: Specimens were printed on the MMSL machine with two distinct photopolymers.
Testing: Tensile tests were performed on an Zwick Z050, the unfiltered results are available in this dataset.
Prediction: Results of tensile tests were used to build models and predict the results of all 60 unique combinations.
Validation: Predictions were compared agains the later tested validation set.
Technical details
The dataset is split into 4 sections: Boundary Represented Geometries (B-rep), Voxel Represented Geometries (V-rep), Results and R-Processing
The B-rep geometries can be opened with any compatible software, as unit for the .STL files mm was utilized. The V-rep files can be opened layer per layer with any image viewer. Results are available for Microsoft Excel. The processing files are written in R and can be inspected by any text-editor or executed with R-Studio.
Using the R-Project
Open the project in RStudio
To modify the filter method or other basic properties, edit R_Setup.R
Run Filter_Overview.qmd to apply the filtering logic and evaluate its effect
Run Data_Overview.qmd to get an overview of the data after filtering
Run any of the Analysis_Pipelines to run the respective machine learning method
If R-Studio is unavailable, existing results can be reviewed by opening the .html files with any browser
Further details
If you use the dataset, please cite the original paper!
Changelog
Version 1: Initial Upload of the Dataset
Version 2:
Added nanoindendation results (Nanoindendation.xlsx)
Added additional tenisile test results (Tensile_Tests_5.xlsx)
Removed predictions and models, as they are dependent on the setup of the R-project (Model_Results_Detailed.xlsx, All_Predictions_Detailed.xlsx)
Rewritten the complete R-Processing: Includs different filtering methods and statistical model methods now, split overall several files
Updated this description with information how the R-Project can be used and added the changelog