Per: Rinaldo henrique pedrini (Arcelormittal pecem), Henrique Severiano de Jesus (ArcelorMittal Tubarão), Fernando Generoso Neiva Ferreira (Arcelormittal tubarão), Sirlene Trugilho Perin Passigatti (Arcelormittal tubarão), Vitor Bogaci Ney (Arcelormittal tubarão), Estefano Aparecido Viera (IFES - Instituto federal do espírito santo)
Abstract:
Steel industries have been carrying out studies, seeking to improve their processes, aiming to serve the market that has been demanding increasingly strict requirements regarding quality and cleanliness. A very common type of defect that has been constantly studied is non-metallic inclusion (NMI), which directly affects the mechanical properties of products. The origin of NMI’s can be mainly due to steel deoxidation, slag dragging in the process, degradation/chemical reactions with refractories, and/or solidification. Quality level can be performed by metallographic observations using optical microscope (OM), it is the most traditional method. Another NMI analysis is throughout Spark-DAT system, which consists of hardware, software, and algorithms installed in an optical emission spectrometer. The aim of this work was to show that Spark DAT can anticipate, with good predictability, the level of NMI’s that will be found in samples in the coils, reducing the analysis time. Thus, the main purpose of this work was to use Spark-DAT to validate its results according to the standards OM methodologies, using samples from ArcelorMittal Tubarão workshop. Representative samples from 4 steels were collected in continuous casting, and hot rolled coils. The results were promising and have shown that is feasible to enable the Spark-DAT technique as a rely on tool to predicting the amount, size, and type of NMI’s that will be found in the coil accordingly to the DIN 50602 standard.
