geometrical rules. These methods work well for many prac- tical applications. However, the applications of microstruc- ture parameters, obtained from the optical image of random two-dimensional planes, have significant limitations.


The first and most important limitation is that the obtained two-dimensional data does not represent the real three-di- mensional structure parameters. Another limitation is due to the optical imaging technique, especially for small particles (less than 1-2 µm). In ductile iron for example, observed par- ticles with less light reflection than the metal matrix repre- sent random sections of the graphite nodules and the other structural features, such as micro-porosity and non-metallic inclusions. Because optical imaging does not separate these features, the optical data is overloaded by small particles


A combination of automated SEM/EDX analysis and the 2D-3D conversion methods was suggested8


(less than 5-10 µm) counted as graphite. Automated SEM/ EDX analysis separates the carbon containing phase from non-metallic inclusions and porosity by applying a special rule, for example, “Graphite – if C>30%”. The tests (Fig. 5) showed that the “noise” from non-metallic inclusions in- creased with decreasing the total graphite nodule number per unit area.8


to ana-


lyze the actual three-dimensional graphite nodule distribu- tion in ductile iron castings produced by different processes. The suggested 2D-3D converter is based on the assumption that any 3D graphite nodule distribution in casting (3Dcasting is a combination of several normal distributions ∑3Dn


) (n=12


in this study). These arbitrarily chosen normal distributions were virtually 2D-cut using stereoscopy rule, summarized


(a)


(b)


(c)


Figure 2. Different types of non-metallic inclusions located inside graphite nodules. International Journal of Metalcasting/Volume 8, Issue 2, 2014 43


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