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White Paper - Materials data for faster, cheaper, more repeatable additive manufacturing (Granta MI for AM)

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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

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