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Wyświetlanie 1-2 z 2
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
Tytuł:
Developing a Methodology for Building the Knowledge Base and Application Procedures Supporting the Process of Material and Technological Conversion
Autorzy:
Wilk-Kołodziejczyk, Dorota
Jaśkowiec, Krzysztof
Bitka, Adam
Pirowski, Zenon
Grudzień-Rakoczy, Małgorzata
Chrzan, Konrad
Małysza, Marcin
Doroszewski, Maciej
Powiązania:
https://bibliotekanauki.pl/articles/2134111.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
artificial intelligence
material conversion
technological conversion
selection of parameters
prediction of mechanical properties
Opis:
The article presents the developed IT solutions supporting the material and technological conversion process in terms of the possibility of using the casting technology of selected alloys to produce products previously manufactured with the use of other methods and materials. The solutions are based on artificial intelligence, machine learning and statistical methods. The prototype module of the information and decision-making system allows for a preliminary assessment of the feasibility of this type of procedure. Currently, the selection of the method of manufacturing a product is based on the knowledge and experience of the technologist and constructor. In the described approach, this process is supported by the proprietary module of the information and decision-making system, which, based on the accumulated knowledge, allows for an initial assessment of the feasibility of a selected element in a given technology. It allows taking into account a large number of intuitive factors, as well as recording expert knowledge with the use of formal languages. Additionally, the possibility of searching for and collecting data on innovative solutions, supplying the knowledge base, should be taken into account. The developed and applied models should allow for the effective use and representation of knowledge expressed in linguistic form. In this solution, it is important to use methods that support the selection of parameters for the production of casting. The type, number and characteristics of data have an impact on the effectiveness of solutions in terms of classification and prediction of data and the relationships detected.
Źródło:
Archives of Metallurgy and Materials; 2022, 67, 3; 1085--1091
1733-3490
Pojawia się w:
Archives of Metallurgy and Materials
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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