3D study of non-metallic inclusions by EEmethod and use of statistics for the estimationof largest size inclusions in tool steel.

Abstract: The control of non-metallic inclusions is very important for the improvement of performance during the application of tool steel. This present study was performed to see the effect of changing of some process parameters during the vacuum degassing of the melt and how these changing parameters affects the characteristics of inclusions in tool steel. The main parameters that were changed during the vacuum degassing were the change of induction stirring, argon flow rate from both the plug 1 and 2 and different ladle ages for different heat. Electrolytic extraction method was used to observe the morphology and characteristics of inclusions as a 3 dimensional view in tool steel. Four lollipop samples from four different heats were used for the experiment and all the samples were after vacuum (AV) degassing. In this study four different types of inclusions were found and they are classified as type 1, 2, 3 and 4. Of them type 1 inclusion was the major one with mostly spherical shaped. This study shows that among the three parameters, induction stirring has the biggest effect for the total number of inclusions per volume in the sample than the other two parameters Heat 4A showed the lowest number of inclusions per volume comparing with the other heats. The main reason behind this can be said that the induction stirring was the lowest comparing with the other heats with moderate argon flow and ladle age of 12. Extreme value analysis was used in this study to predict the probability of getting largest size inclusions in a certain volume of the metal. For the prediction of the largest inclusion size, both the electrolytic extraction (3D) and cross-sectional (2D) method was used. Later in this study comparison was done to determine the accuracy of both the methods and it is concluded that for the type 1 inclusions electrolytic extraction method shows almost similar trend with cross-sectional method and electrolytic extraction method shows better accuracy for the prediction of largest size inclusions than the cross-sectional method. Electrolytic Extraction method is also applicable for the prediction of largest size inclusions for multiple types of inclusions.