2019 : Neural network model for profile temperature of nickel kiln

Totok Ruki Biyanto S.T., M.T., Ph.D.


Abstract

Reduction Kiln plays a very important role in the nickel smelting process. As multi-variable processing and nonlinear system, nickel kiln is difficult to be maintain in the best performance. While research on this area is very rare for this industry is such specific and unique. In this paper, it is proposed time-series neural network model for nickel kiln, with an approach based on Nonlinear Auto Regressive with eXogenous input (NARX). This model provides prediction of input-output data set to achieve certain operating condition, especially profile temperature alongside the kiln. Input-output data set of real plant was collected from Kiln 5 in PT Vale Indonesia for along 2018. The data set was reviewed and chosen for the neural network model. It was achieved that regression of the model is 0.999 which is proving that there is strong relationship between input and output. While mean squared error (MSE) is 16.4077, which …