INTER-LABORATORY STUDY OF NODULARITY AND NODULE COUNT OF DUCTILE IRON BY IMAGE ANALYSIS
Serge Grenier and Chantal Labrecque Rio Tinto Iron and Titanium, Sorel-Tracy, QC, Canada
Amit Bhattacharjee
John Deere, Waterloo, IA, USA Richard Gundlach
Element, Wixom, MI USA Bente Kroka
Elkem Technology, Kristiansand, Norway Mike Riabov
Neenah Foundry, Neenah, WI, USA Copyright © 2014 American Foundry Society
A version of this paper was previously published in the 2013 Keith Millis Symposium Proceedings Abstract
Image analysis has become an increasingly important an- alytical tool to facilitate the determination of nodularity and nodule count in ductile iron. This paper summarizes the im- age analysis results obtained by several laboratories on iden- tical samples having different nodularity and nodule count. The parameters studied include; the number of particles ana- lyzed, the effect of the trap size and varying the shape factor.
Introduction
The mechanical properties of ductile irons (DI) are inti- mately linked to their microstructures.1-4
For a DI casting,
the most common microstructural characterization param- eters are; nodule count, nodularity, and pearlite content. A buyer might require the casting to meet the tensile and yield strengths and elongation associated with a given DI grade, or might simply ask that the casting achieves a minimum nodule count or nodularity, or specify that the percentage of pearlite does not exceed a maximum value, or all of the above. These microstructural parameters can be determined with the help of visual charts, but the human interpretation factor and the limited number of fields of view analyzed by eyes can both lead to substantial errors.
Image analysis (IA) systems hold the promise to minimize these errors, and as such,5
have become an increasingly
important analytical tool to facilitate the determination of nodularity and nodule count in ductile iron. However, IA systems require the user to select a wide variety of analytical parameters (trap size, shape factor, magnification, number of fields analyzed, etc.) all of which impact the final results and are poorly understood. Furthermore, the lack of availability
International Journal of Metalcasting/Volume 8, Issue 2, 2014
This paper summarizes the effect of varying some analytical parameters on the IA results obtained, and compares the IA results obtained by several laboratories on identical samples having different nodularity and nodule count. In essence, the inter-laboratory study (ILS) presented here simulates the type of errors that can be expected when an IA user requests a sam- ple re-analysis from another IA user. The parameters studied include the number of particles analyzed, the effect of the trap size, the magnification used and varying the shape factor.
Image Analysis Procedure
Samples must be polished prior to undergoing an IA. If the percent pearlite or carbides are required, then the samples must be etched to reveal these phases. However, the deter- mination of the nodule count and the nodularity of a sample are best achieved on un-etched samples.
The IA system starts looking at all the “features” apparent on the polished surface. At this point of the analysis, these
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Keywords: ductile iron, image analysis, nodule count, nodu- larity, inter-laboratory study, inter-laboratory study (ILS)
Note: This paper uses the comma symbol as a radix point to designate a fraction (i.e. 1,5) instead of the more conven- tional decimal point.
of DI image analysis standards, coupled with the absence of published inter-laboratory comparative studies, leads to IA results for which the accuracy is highly uncertain.
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