Monografia (especialização)
Análise estatística do comportamento térmico na região intermediária do molde de uma máquina de lingotamento contínuo de placas para predição de rompimento de pele.
Fecha
2020-08-07Autor
Alexandre de Freitas Gomes de Mendonça
Institución
Resumen
The need for reliability in steelmaking process is permanently increasing. In this context, Usiminas has focused its efforts, at the steelmaking plants, towards continuously improving its processes, consequently ensuring greater operational stability. The continuous casting is responsible for the controlled solidification of liquid steel. The solidification begins in the mold where a shell, which sustains the liquid through the machine, is formed. Breakout of this shell is the most relevant problem in continuous casting process. The liquid steel breaks the solid shell and leaks to the strand, reaching the electromechanical parts of the machine, therefore offering risks to the workers, potentially interrupting the sequence, generating scrap and stopping the equipment for a while. To avoid such occurrence, a Breakout Detection System (BDS) is used which continuously monitors the thermal parameters of the mold through strategically positioned thermocouples. Based on mapped deterministic thermal failure behaviors, it was possible to establish activation criteria and reduce the casting speed to a safe condition. In the literature it is presented that the most frequent failure mode is by sticking in the mold, however with exploratory data analysis and use of Control Charts, it was possible to identify a peculiar pattern of failure in the continuous casting machines at Usiminas Ipatinga and establish innovative criteria for activation of the Breakout Detection System. The assessment of the probability of an alarm occurring once per month based on this new characteristic is less than 1,82·E-6. However, such activation removes a point of vulnerability from the Breakout Detection System (BDS) and places it at an upper level of operational safety, thanks to exploratory data analysis.