Linear programming and methods of multivariate regression applied to the prediction of the refractory campaign duration in a steel company

Citation:

Dalila Rodrigues Baesso, Marco Antônio Bonelli Júnior, and Julio César Alvarenga. 2019. “Linear programming and methods of multivariate regression applied to the prediction of the refractory campaign duration in a steel company.” In LI SBPO - Simpósio Brasileiro de Pesquisa Operacional, 2: Pp. 107721. Limeira, SP. Publisher's Version

Abstract:

When it comes to steel processes, it is known that refractory materials are responsible for a significant portion of the steel production costs. For this reason, this work aimed to understand the high variability and the low durability of the refractory campaign that compose a process of continuous casting in a large LD mill in the state of Minas Gerais , identifying the relationship between the process variables so it was possible to make estimates about the duration of its refractory campaign. For the selection of the explanatory factors, a variation of the method Stepwise was used. In each step of the algorithm, a model based on linear programming was responsible for the calculations of the linear regression coefficients. In the end, a prediction model was obtained for the duration of the campaign containing 12 explanatory factors and 97.66% of statistical significance.