3
Using Materials Data for Faster, Cheaper, More Repeatable Additive Manufacturing //
Figure 3: Data management for AM production and testing using Granta MI
/ 2) Efficient data analytics drives the technical decision-making pr ocess
With all the data in one place, it is important to visualize the data and understand the relationships between various datasets using suitable
analytics tools. This will help you understand how it is influencing the material properties and part quality. One such analytics tool is the
Granta MI MatAnalyzer application.
Some example scenarios when using Granta MI MatAnalyzer could be:
A. Generate comparison charts. Test results by comparing powder chemistries with process parameters (see Figures 4-A and 5).
B. Use curve fitting (spline, linear, quadratic, cubic… up to 10
th
degree polynomial) to generate curves. Data from test results can
then be exported back to Granta MI. (Figure 4-B)
C. Visualize multi-dimensional data (Fig 4-C)
D. Generate statistics: Mean, max, min, median, range STD, box plot, curve averaging (Figure 4-D).
Figure 4: Examples of the various types of analysis of AM data using the Granta MI MatAnalyzer app.
A
Powder
Characteristics
vs process
parameters
vs material
strength
C
Build Location
vs Strength
D
Basic
Statistical
Plots
B
Curve Fitting
to data points
