@ARTICLE{Jaśkowiec_K._Prediction_2023,
 author={Jaśkowiec, K. and Opaliński, A. and Kustra, P. and Jach, D. and Wilk-Kołodziejczyk, D.},
 volume={vol. 23},
 number={No 2},
 journal={Archives of Foundry Engineering},
 pages={137-144},
 howpublished={online},
 year={2023},
 publisher={The Katowice Branch of the Polish Academy of Sciences},
 abstract={The structure of Austempered Ductile Iron (ADI) is depend of many factors at individual stages of casting production. There is a rich literature documenting research on the relationship between heat treatment and the resulting microstructure of cast alloy. A significant amount of research is conducted towards the use of IT tools for indications production parameters for thin-walled castings, allowing for the selection of selected process parameters in order to obtain the expected properties. At the same time, the selection of these parameters should make it possible to obtain as few defects as possible. The input parameters of the solver is chemical composition Determined by the previous system module. Target wall thickness and HB of the product determined by the user. The method used to implement the solver is the method of Particle Swarm Optimization (PSO). The developed IT tool was used to determine the parameters of heat treatment, which will ensure obtaining the expected value for hardness. In the first stage, the ADI cast iron heat treatment parameters proposed by the expert were used, in the next part of the experiment, the settings proposed by the system were used. Used of the proposed IT tool, it was possible to reduce the number of deficiencies by 3%. The use of the solver in the case of castings with a wall thickness of 25 mm and 41 mm allowed to indication of process parameters allowing to obtain minimum mechanical properties in accordance with the PN-EN 1564:2012 standard. The results obtained by the solver for the selected parameters were verified. The indicated parameters were used to conduct experimental research. The tests obtained as a result of the physical experiment are convergent with the data from the solver.},
 type={Article},
 title={Prediction of Selected Mechanical Properties in Austempered Ductile Iron with Different Wall Thickness by the Decision Support Systems},
 URL={http://journals.pan.pl/Content/127783/PDF/AFE%202_2023_19_final%20version.pdf},
 doi={10.24425/afe.2023.144306},
 keywords={Solver, ADI, Prediction, Decision tree},
}