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    Wyświetlanie 1-4 z 4
    Tytuł:
    Information and Decision System Supporting the Production of ADI Cast Iron Products
    Autorzy:
    Opaliński, Andrzej
    Wilk-Kołodziejczyk, Dorota
    Powiązania:
    https://bibliotekanauki.pl/articles/2049745.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    decision support
    information system
    ADI casting
    austempered ductile cast iron
    ADI
    Opis:
    The presented article concerns the issue of supporting the ADI cast iron product manufacturing process and presents an IT system dedicated mainly to designers and technologists. Designers can be supported at the stage of selecting types of materials and technologies (including ADI cast iron) to produce products with required properties. Technologists can obtain support in determining the parameters (temperature and chemical) of the ADI cast iron manufacturing process in order to obtain products with specific properties. The system also contains an information resources (standards, documentation, examples) concerning ADI cast iron and products made of it. Examples of use by individual system users are presented as a case study.
    Źródło:
    Archives of Metallurgy and Materials; 2021, 66, 2; 651-657
    1733-3490
    Pojawia się w:
    Archives of Metallurgy and Materials
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Artificial Neural Networks as a Tool for Supporting a Moulding Sand Control System Based on the Dependency between Selected Moulding Sand Properties
    Autorzy:
    Mrzygłód, Barbara
    Jakubski, Jarosław
    Opaliński, Andrzej
    Regulski, Krzysztof
    Powiązania:
    https://bibliotekanauki.pl/articles/24201264.pdf
    Data publikacji:
    2023
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    artificial neural network
    decision support
    green moulding sand
    compactibility
    Opis:
    The article presents the potential for using artificial neural networks to support decisions related to the rebonding of green moulding sand. The basic properties of the moulding sand tested in foundries are discussed, especially compactibility as it gives the most information about the quality of green moulding sand. First, the data that can predict the compactibility value without the need for testing are defined. Next, a method for constructing an artificial neural network is presented and the network model which produced the best results is analysed. Additionally, two applications were designed to allow the investigation results to be searchable by determining the range of values of the moulding sand parameters.
    Źródło:
    Journal of Casting & Materials Engineering; 2023, 7, 2; 15--21
    2543-9901
    Pojawia się w:
    Journal of Casting & Materials Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Bainite transformation time model optimization for Austempered Ductile Iron with the use of heuristic algorithms
    Autorzy:
    Olejarczyk-Wożeńska, Izabela
    Opaliński, Andrzej
    Mrzygłód, Barbara
    Regulski, Krzysztof
    Kurowski, Wojciech
    Powiązania:
    https://bibliotekanauki.pl/articles/29520068.pdf
    Data publikacji:
    2022
    Wydawca:
    Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
    Tematy:
    heuristic optimization
    bainite
    ADI
    Particle Swarm Optimization
    Evolutionary Optimization Algorithm
    Opis:
    The paper presents the application of heuristic optimization methods in identifying the parameters of a model for bainite transformation time in ADI (Austempered Ductile Iron). Two algorithms were selected for parameter optimization – Particle Swarm Optimization and Evolutionary Optimization Algorithm. The assumption of the optimization process was to obtain the smallest normalized mean square error (objective function) between the time calculated on the basis of the identified parameters and the time derived from the experiment. As part of the research, an analysis was also made in terms of the effectiveness of selected methods, and the best optimization strategies for the problem to be solved were selected on their basis.
    Źródło:
    Computer Methods in Materials Science; 2022, 22, 3; 125-136
    2720-4081
    2720-3948
    Pojawia się w:
    Computer Methods in Materials Science
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Prediction of Selected Mechanical Properties in Austempered Ductile Iron with Different Wall Thickness by the Decision Support Systems
    Autorzy:
    Jaśkowiec, Krzysztof
    Opaliński, Andrzej
    Kustra, Piotr
    Jach, D.
    Wilk-Kołodziejczyk, Dorota
    Powiązania:
    https://bibliotekanauki.pl/articles/27314159.pdf
    Data publikacji:
    2023
    Wydawca:
    Polska Akademia Nauk. Czasopisma i Monografie PAN
    Tematy:
    ADI
    austempered ductile iron
    mechanical properties
    prediction
    decision support systems
    decision tree
    żeliwo sferoidalne
    właściwości mechaniczne
    prognozowanie
    systemy wspomagania decyzji
    Opis:
    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.
    Źródło:
    Archives of Foundry Engineering; 2023, 23, 2; 137--144
    1897-3310
    2299-2944
    Pojawia się w:
    Archives of Foundry Engineering
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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