The use of modern casting materials allows the achievement of higher product quality indices. The conducted experimental studies of new materials allow obtaining alloys with high performance properties while maintaining low production costs. Studies have shown that in certain areas of applications, the expensive to manufacture austempered ductile iron (ADI) can be replaced with ausferritic ductile iron or bainitic nodular cast iron with carbides, obtained without the heat treatment of castings. The dissemination of experimental results is possible through the use of information technologies and building applications that automatically compare the properties of materials, as the machine learning tools in comparative analysis of the properties of materials, in particular ADI and nodular cast iron with carbides.
The application of data mining techniques in the design of modern foundry materials allows achieving higher product quality indicators. Designing of a new product always requires thorough knowledge of the effect of alloying elements on the microstructure and hence also on the properties of the examined material. The conducted experimental studies allow for a qualitative assessment of the indicated relationships, but it is the use of intelligent computational techniques that enables building an approximation model of the microstructure and, owing to this, make predictions with high precision. The developed model of prediction supports the technology-related decisions as early as at the stage of casting design and is considered the first step in selecting the type of material used.
The object of the conducted experimental studies was determination of the physical properties of the BA1044 alloy subjected to several types of toughening and modification under varying conditions. The aim of the experiments was to determine which of the above mentioned technological processes has greater impact on the value of the alloy parameters and how these treatments should be chosen to get the metal with the desired properties on a limited number of experiments.Keywords: Copper alloys, knowledge model, inference methods, artificial intelligence, heuristicsPrzedmiotem prowadzonych badań eksperymentalnych było określenie właściwości fizycznych stopu BA1044 poddanego kilku rodzajom ulepszania cieplnego oraz przy różnych warunkach modyfikacji. Celem eksperymentu było określenie, które ze wspomnianych zabiegów technologicznych posiadają największy wpływ na wartości badanych parametrów metalu oraz w jaki sposób należy dobierać te działania aby uzyskać metal o pożądanych właściwościach przy ograniczonej liczbie eksperymentów.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.