Studies were carried out to determine the effect of heat treatment parameters on the plastic properties of unalloyed ausferritic ductile iron,
such as the elongation and toughness at ambient temperature and at – 60 °C. The effect of austenitizing temperature (850, 900 and 950°C)
and ausferritizing time (5 - 180 min.) at a temperature of 360°C was also discussed. The next step covered investigations of
a relationship that is believed to exist between the temperature (270, 300, 330, 360 and 390 °C) and time (5, 10, 30, 60, 90, 120, 150, 180,
240 min.) of the austempering treatment and the mechanical properties of unalloyed ausferritic ductile iron, when the austenitizing
temperature is 950°C. The “process window” was calculated for the ADI characterized by high toughness corresponding to the EN-GJS800-10-RT
and EN-GJS-900-8 grades according to EN-PN 1564 and to other high-strength grades included in this standard. Low-alloyed
cast iron with the nodular graphite is an excellent starting material for the technological design of all the ausferritic ductile iron grades
included in the PN-EN-1624 standard. The examined cast iron is characterized by high mechanical properties stable within the entire range
of heat treatment parameters.
This paper shows how it is possible to obtain an ausferrite in compacted graphite iron (CGI) without heat treatment of castings. Vermicular graphite in cast iron was obtained using Inmold technology. Molybdenum was used as alloying additive at a concentration from 1.6 to 1.7% and copper at a concentration from 1 to 3%. It was shown that ausferrite could be obtained in CGI through the addition of molybdenum and copper in castings with a wall thickness of 3, 6, 12 and 24 mm. Thereby the expensive heat treatment of castings was eliminated. The investigation focuses on the influence of copper on the crystallization temperature of the graphite eutectic mixture in cast iron with the compacted graphite. It has been shown that copper increases the eutectic crystallization temperature in CGI. It presents how this element influences ausferrite microhardness as well as the hardness of the tested iron alloy. It has been shown that above-mentioned properties increases with increasing the copper concentration.
The herein paper contains the results of investigations on a new type of cellulose blend used for the manufacture of profiles applied in the
process of making gating systems in the foundry industry. A standard cellulose profile was subjected to an experiment. During the
experiment the profile was filled with a liquid cast iron and at the same time the temperatures of the liquid metal crystallizing inside the
profile were measured as well as the temperature of the outer layer of the profile was controlled. Further, the microstructure of the cast
iron, which crystallized out inside the cellulose profile, was analysed and the cellulose, thermally degraded after the experiment, was
verified with the use of the chemical analysis method. Moreover, a quality analysis of the original as well as the degraded cellulose profile
was run with the use of the FTIR infrared spectroscopy. The presented results revealed that the cellulose blend is aluminium silicate
enriched and contains organic binder additives. The cast iron, which crystallized out, tended to have an equilibrium pearlitic structure with
the release of graphite and carbides. The generation of disequilibrium ausferrite phases was also observed in the structure.
This article presents the methodology for exploratory analysis of data from microstructural studies of compacted graphite iron to gain
knowledge about the factors favouring the formation of ausferrite. The studies led to the development of rules to evaluate the content of
ausferrite based on the chemical composition. Data mining methods have been used to generate regression models such as boosted trees,
random forest, and piecewise regression models. The development of a stepwise regression modelling process on the iteratively limited
sets enabled, on the one hand, the improvement of forecasting precision and, on the other, acquisition of deeper knowledge about the
ausferrite formation. Repeated examination of the significance of the effect of various factors in different regression models has allowed
identification of the most important variables influencing the ausferrite content in different ranges of the parameters variability.
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