Historical Version s - view previous versions of standard. More E Although compositions are not identified, Microscopic methods place inclusions into one of several composition-related categories sulfides, oxides, and silicates—the last as a type of oxide. Paragraph Only those inclusions present at the test surface can be detected.
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Superior steel quality is critical for a variety of industries and applications, especially for the manufacture of vehicles and ships and construction of buildings. Reliable and precise evaluation methods for non-metallic inclusions are key to determining their influence on the quality of steel. The combination of the LAS X Steel Expert software and a Leica microscope enables users to attain a customizable, accurate, and efficient solution for rating non-metallic inclusions contained in steel.
Optimal ways to analyze the quality of steel, whether low carbon, stainless, or high alloyed, are described. The quality of steel is essential for industries like automotive, transportation, metalworking, electric power, and construction.
To ensure the highest standards, an accurate and reliable quality assurance workflow for the inspection of non-metallic inclusions is critical. These 3 main points are important for the optimization of incluson detection and analysis during steel production:. Leica Microsystems offers state-of-the-art and customizable microscopy solutions, using the LAS X Steel Expert software, for inspecting the microstructure and evaluating the non-metallic inclusion content of steel.
They range from manual inspection to fully motorized solutions, whichever is optimal for the necessary workload. Present-day methods of steel production are unable to attain an alloy free of non-metallic inclusions. So inclusions are present in all steels to a greater or lesser extent depending on the raw materials and production methods used.
The quality of steel is influenced by its composition and the melting and processing methods, but also by the properties size, shape, hardness, and chemical composition of non-metallic inclusions present within it.
There can be a large variation in the properties of steel inclusions even within the same production batch. For this reason, different analysis methods for inclusions have been developed and are now commonly in use.
These methods make it possible to determine accurately the composition, structure, and amount of non-metallic inclusions in steel. Non-metallic inclusions are foreign substances in steel which can have a very complex appearance refer to figure 1 and 2. During production, deformation often occurs from rolling, forging or stamping. It has been shown that deformation of steel with non-metallic inclusions can induce cracks and fatigue failure.
Traditionally, inclusions are categorized by composition, but also their origin as either endogenous or exogenous. Endogenous inclusions form in steel when trace amounts of non-metallic elements, mainly nitrogen N , oxygen O , phosphorous P , and sulfur S , are present. The majority of inclusions in steels are oxides and sulfides.
Usually, the amount of phosphorus is quite small, so phosphide inclusions are seldom. The composition of oxide inclusions covers a very wide range of binary, ternary and even quaternary compounds which are complex mixtures based mainly on aluminum oxides alumina or aluminates or silicon oxides silica or silicates.
Exogenous inclusions are caused by the entrapment of external contaminants and their source can include slag, dross, flux residues, and pieces from molding materials. Cleanliness indicates the steel has been processed by different techniques to reduce the amount of inclusions and their associated risks. Clean steel exhibits a maximum of 60 parts per million ppm 0. Hydrogen does not form inclusions, but can lead to embrittlement from its diffusion into the metal matrix and eventually premature fracture.
It is particularly a problem for high-strength steels. The presence of aluminates may result in poor fatigue properties, while silicates are detrimental if the steel has to undergo heat treatment at a later stage. Usually the amount of non-metallic inclusions in steel is less than 0.
However, the number of inclusions is still very high because of their very small size. For instance, in 1 kg of a standard quality, aluminum killed, low carbon steel there are 0.
In terms of size, there are approximately:. In addition to sulfides and oxides, nitrides are present in special steels that contain elements with a high affinity to nitrogen N , like titanium Ti. Titanium is a less expensive alloying element and is increasingly used to refine grain size and improve mechanical properties of steel alloys.
As a result, titanium nitride inclusions in steel are ever more common refer to figure 3. The most recent standard, EN see section just below , incorporates titanium nitride inclusions in the rating method. The required steel quality depends on the type of application for which it is used. Non-metalic inclusions certainly have an effect on the quality of steel, but some types have more of an effect than others.
The chart below figure 4 depicts the chronological development of the standards. In , all national standards from European countries, like DIN  and NF A  , were officially withdrawn and replaced by EN  , except for the Swedish standard, SS , which was re-issued last year with new JK rating charts . It was the first test method eighty years ago and seems still to have much life ahead of it.
Currently, the main international and regional standards which address test methods and practices for the evaluation of non-metallic inclusions in steel are ASTM E45  , EN , and ISO  refer to table 2. ASTM E45 is the principal test method, but other standards, such as ASTM E  and ASTM E  , are available for particular cases, like determining the inclusion content with stereological methods and inclusion rating using electron microscopes.
ASTM E  describes a methodology to statistically characterize the distribution of the largest endogenous non-metallic inclusions based on quantitative metallographic measurements. This practice applies a statistical approach to estimate the extreme value distribution of inclusions in steels. In fact, a new version of EN has been issued at the beginning of the year with relevant changes to facilitate its adoption by the European steel market.
ASTM E provides a guide for preparing and evaluating samples for the assessment of non-metallic inclusions by automatic image analysis methods. ISO explains inclusion assessment by macroscopic methods. Steel -- Determination of content of non-metallic inclusions -- Micrographic method using standard diagrams. Table 2: International and regional standards for characterization of steel quality in terms of non-metallic inclusions.
To assess the type, number, and size of inclusions in the steel, comparisons between reference images for each group and a live microscope image of a steel sample were made. Today, most, but not all, of the modern standards use these same 4 classification groups, A to D. However, for the modern standards, color and morphological parameters are used to define and classify inclusions into these four groups A to D. Besides length and width for non-round particles and diameter for round ones, other features like aspect ratio, contour, and horizontal and vertical distance between particles are used to differentiate inclusions refer to figure 5.
For classification with DIN  , a different nomenclature is used. This first peculiarity of the DIN standard arises from the fact that in some steels the degree of deformation is not high enough to fully dissolve aluminate-type inclusions. They will appear similar to elongated, streak-like oxides. Thus, a naming convention without composition bias was selected for the standard.
The size classification of inclusions with respect to inclusion types separates them into a severity level that purely depends on the inclusion surface area. The inclusion area is measured using microscopy. The size class is defined by:. The range for each size class is defined by:. However, since humans have trouble to judge areas by eye, in the DIN a visual aid comparison chart is available. This chart displays the four basic inclusion types with respective examples for the individual size classes.
It also introduces 6 additional inclusion subtypes and a rating scheme based on inclusion length. Based on a typical width per inclusion of a certain class size, additional finer and larger inclusion series are displayed in the comparison chart, leading to a unique, diagonal relationship between inclusion subtypes and main inclusion types refer to figure 7. The main types are relevant for the size class rating. Due to the peculiarity of the main DIN comparison chart seen in figure 7, when it is used in combination with other comparison charts highlighting different inclusion characteristics, then inadvertently its use for inclusion rating by visual inspection may lead to more confusion than clarity.
Although still widely used on an international basis, the DIN standard is probably often at least partially misunderstood and frequently misinterpreted. The new European standard differs substantially from the others as it is not derived from traditional methods, but rather mathematical principles. This approach has some benefits, for instance easier implementation of automated image analysis methods and a comprehensive definition and classification even when doing manual evaluation. However, one disadvantage is that comparison with results obtained with other standards is difficult.
The physical correlation between the standard results and inclusions leads to some controversy that has prevented the rapid adoption and common use of EN  by industry experts.
EN inclusion categories The standard EN classifies inclusions first by color gray level , then by shape elongated or globular , and finally by arrangement scattered or aligned. The field of view is adjusted to a square of 0. The typical workflow for the rating of inclusions with microscopic methods is shown in figure 10 below. The workflow starts with sampling, i. Sample preparation has a great influence on the reproducibility of the analysis and quality of the results, particularly with automated rating solutions.
The next step involves selecting the analysis procedure to be done in accordance with a standard method worst field, worst inclusion, statistical analysis, etc. Once a method is applied, the results reported should include a classification table with the severity level or index calculated according to the standard.
Metallographic sample preparation refer to figure 11 for non-metallic inclusion analysis can be challenging, because there is no etching at the end and the polishing step should result in a flat surface without scratches and other defects, such as holes or pull-outs, pitting, and comet tails refer to figure The risk is a distorted sample shape.
In steels without heat treatment, it gives good results to quench and temper the samples to harden the matrix and avoid defects. Machine grinding is recommended after hardening to maintain a surface unaffected by oxidation or decarburization. As explained in ASTM E, a microscope equipped with differential interference contrast DIC illumination refer to figure 13A and capable of magnification values between x and x should be used during the sample preparation procedure to verify the true surface appearance.
At x, narrow bright lines indicating ditches at some inclusion edges could be seen figure 13B. A method to determine whether these ditches will be detected by the image analysis system involves slowly rotating the polarizer item 6 in figure 13A from the extinction position to see if there is any apparent motion of the inclusion edges.
If the transition from DIC to brightfield changes these ditches from bright to dark, this result indicates poor sample preparation. The risk of poor sample preparation is that the inclusion could be measured to be larger than its actual size. Even tiny scratches from final polishing will usually be seen under DIC at x. Normally, these scratches vanish upon rotation of the polarizer and will not affect the inclusion rating at lower magnification.
In addition, the software will automatically remove most of them as artifacts, even if they are still visible. Oblique light is also a valid alternative to see height differences, although it cannot give any color information.
Once the sample preparation method is optimized, then the assessment procedure can be selected. Provided careful sample preparation is done beforehand, a reproducible analysis of entire samples is possible even when the user leaves the system unattended. Results are unbiased and the automated analysis methods are compliant with the international and regional standards already mentioned above. Advanced review capabilities enable discernment between types of inclusions or inclusions and artifacts.
The software makes all standards available for comparison during a single scan.
ASTM E-45 Inclusion Content of Steel
Superior steel quality is critical for a variety of industries and applications, especially for the manufacture of vehicles and ships and construction of buildings. Reliable and precise evaluation methods for non-metallic inclusions are key to determining their influence on the quality of steel. The combination of the LAS X Steel Expert software and a Leica microscope enables users to attain a customizable, accurate, and efficient solution for rating non-metallic inclusions contained in steel. Optimal ways to analyze the quality of steel, whether low carbon, stainless, or high alloyed, are described. The quality of steel is essential for industries like automotive, transportation, metalworking, electric power, and construction. To ensure the highest standards, an accurate and reliable quality assurance workflow for the inspection of non-metallic inclusions is critical.
Standard Test Methods for Determining the Inclusion Content of Steel 1
Over the years, ASTM Committee E-4 on Metallography has conducted interlaboratory test programs to evaluate the precision and bias associated with measurements of microstructure using proposed and existing test methods. ASTM decided in the late s that all test methods that generated numerical data must have a precision and bias section defining the repeatability and reproducibility of the method. Defining bias associated with a test method is difficult unless there is an absolute known value for the quantity being measured and this is not possible when microstructural features are being measured. The results from 9 people who were reported to be qualified, regular users of the method revealed consistent problems of misclassification of inclusions types and a wide range of severity ratings for each specimen. The charts were designed to determine the size, distribution, number and types of indigenous inclusions naturally occurring particles that form before or during solidification due to limited solid solubility for O and S in steels.
Difficulties Using Standard Chart Methods for Rating Non-Metallic Inclusions
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