Table 4. Repeatability Tests Description
Table 5. Repeatability Test Results
Figure 8. Microstructure of a sample used for the repeatability tests.
Table 6. Particle Count as a Function of Number of Fields Analyzed
particles are the results of the influence of a series of chemi- cal, physical and thermal parameters,3
the predictability of
In Test #3, the same sample was analyzed ten times, but every time, a different set of 25 fields was used. The results were, as expected when compared to Test #1 and #2, larger standard de- viation values. This is a very important point to underline when analyzing the nodularity and nodule count of samples with a nodularity in the 65%-85% range. A sample with a nodularity >95% will most likely be less sensitive to the choice of fields being analyzed than another with a lower nodularity.
One aspect of IA not discussed so far is the influence of using contiguous (touching each other) or non-contiguous (separat- ed from one another) fields. Using non-contiguous fields al- lows the user to “cover” a larger area and thus holds the prom- ise to yield results which represent better the overall sample. To have 25 fields separated from one another, the IA system must apply mathematical algorithms which deal with the situ- ations when a nodule is cut by the field of view. In Test #4, the same set of 25 contiguous fields was analyzed 10 times. The results indicate that the standard deviations obtained in Test #4 are comparable to those of Tests #1 and #2.
Effect of Numbers of Fields
When observed at high magnification (100x and above), a microstructure is, by nature, the result of a local random phe- nomenon. Since the size, shape and number of the graphite
58
, which represents about 0,2% of the total area of the cast bar. Furthermore, a single field examined at 100x will typically contain about 100-250 graphite particles once a 10µm trap size has been applied, depending on the nodule count of the sample. Taking into account the local microstructural fluctuations observed in all samples, using a limited number of fields to calculate a nodularity or nodule count value will lead to significant differences depending on the location of the samples examined (and therefore the lab- oratory conducting the analysis). Intuitively, the more fields of view that are used, the more repeatable will be the results.
Figures 9-11 are graphical representations of the influence of the number of fields of view used on the nodule count value and nodularity (% Area and Number %) obtained for the sample presented in Figure 8 (100x, 10µm trap size, Shape Factor = 0,5 roundness).
Table 6 summarizes the number of particles which were greater than 10µm in dimension, as a function of the number of fields examined. Figures 9-11 indicate that, for a sample of that nodularity, in order to have a result which is repeat- able, the examination of at least 10 fields (>1500 particles) is required.
International Journal of Metalcasting/Volume 8, Issue 2, 2014
the local nodule count and of the nodularity of the sample is impossible. Therefore, when trying to assign either a nodule count or a nodularity value to a sample, one must ensure that a statistically significant number of fields of view have been assessed before a precise conclusion can be achieved. Hav- ing a sufficient number of fields examined implies not only that the number of graphite particles becomes statistically significant, but also that the area examined will be represen- tative of the sample in its entire area of interest. For exam- ple, when trying to determine the microstructural parameters of a 2,3cm (7/8 in.) diameter tensile DI bar at 100x, a single typical field of view analyzed by IA has an area of approxi- mately 0,9 mm2
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