GENETIC PROGRAMMING AND SOFT-ANNEALING PRODUCTIVITY

GENETSKO PROGRAMIRANJE IN PRODUKTIVNOST MEHKEGA ŽARJENJA

Miha Kovačič1, Božidar Šarler2

1ŠTORE STEEL d.o.o., Železarska cesta 3, SI-3220 Štore, Slovenia
2Laboratory for Multiphase Processes, University of Nova Gorica, Vipavska 13, SI-5000, Nova Gorica, Slovenia

miha.kovacic@store-steel.si

Prejem rokopisa – received: 2011-02-02; sprejem za objavo – accepted for publication: 2011-05-20

 

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).

Keywords: steel, soft annealing, furnace productivity, hardness, modeling, genetic programming

 

Zaradi raznolikosti tehnoloških poti je v jeklarski industriji težko izbrati primerne parametre toplotne obdelave. V članku je predstavljen način, kako smo z metodo genetskega programiranja povečali produktivnost žarilne peči. Na podlagi podatkov o trdoti materiala pred mehkim žarjenjem in po njem (222 vzorcev, 24 različnih kvalitet jekla), o hitrosti žarjenja in kemični sestavi (C, Cr, Mo, Ni in V) smo z genetskim programiranjem dobili matematični model trdote materiala po mehkem žarjenju. Model smo preizkusili s testnimi podatki. Na podlagi modela, ki se odmika od eksperimentalnih podatkov za 3,24 % (2,68 % pri testnih podatkih), nam je uspelo hitrost žarjenja povečati s 3,2 m/h na 7 m/h.

Ključne besede: jeklo, mehko žarjenje, produktivnost peči, trdota, modeliranje, genetsko programiranje

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