GENETIC PROGRAMMING AND SOFT-ANNEALING PRODUCTIVITY GENETSKO PROGRAMIRANJE IN PRODUKTIVNOST MEHKEGA ZARJENJA

摘要

An optimal thermo-mechanical processing in the steel industry is difficult because of the multi-constituent and multiphase character of commercial steels, the variety of the possible processing paths and the plant-specific equipment characteristics. This paper shows a successful implementation of the genetic programming approach for increasing the furnace conveyor speed and consequently the higher productivity of the heat-treatment furnace in the soft-annealing process. The data (222 samples covering 24 different steel grades) on a furnace conveyor's speed, the chemical composition of the steel (weight percent of C, Cr, Mo, Ni and V) and the Brinell hardness before and after the soft annealing were collected during daily production. On the basis of the measured data a mathematical model for the hardness after the soft annealing was developed by genetic programming. According to the modelled influences on the hardness, a higher furnace conveyor speed was attempted in practice. The experimental results of the hardness after the soft annealing with the increased conveyor speed and the predictions of the mathematical model were compared with an agreement of 3.24 % (2.68 % at testing data set). The genetic model was also compared and verified with a linear regression model. As a consequence of the used computational intelligence approach, the productivity of the soft-annealing process increased (from the furnace conveyor speed 3.2 m/h to 7 m/h).