The possibility of the boronizing process on the pressed samples of iron powder

Požega, Emina; Ivanov, Svetlana Lj.; Conić, Vesna; Cadjenovic, Branislav

doi:10.2298/hemind0903253p

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“…Adekvatnost matematičkog modela, statistički je proverena analizom varijanse (Analysis of variance -ANOVA) [22]. Ovakav pristup analizi uticajnih parametara, uz primenu odgovarajućeg plana eksperimenta, uspešno je primenjen u modelovanju mnogih metalurških procesa [32][33][34][35][36][37].…”

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Correlation of hardness of aluminum composites obtained by stir casting technology and the size and weight fraction of reinforcing Al2O3 particles

Petrović

Mladenović

Ivanović

et al. 2021

Hem Ind

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In this work, the stir casting method was applied to obtain composites based on the alloy AN EW 6061 used as a metal base, and Al2O3 particles as a reinforcement. Composites play a significant role as engineering materials. Therefore, it is necessary to study, in detail, the production methods and the factors that affect their mechanical properties. For this purpose, we have carried out a planned experiment wi ASM International th the aim to use regression analysis to predict the influence of particle size and mass fraction on hardness of the obtained composites. The full factorial experimental design with two factors was used, which was analyzed at three levels. Hardness was observed as a system response, while particle size and mass fraction were set as influencing factors. Influencing factors were observed at three levels: 50, 80 and 110 ?m for the particle size and 2, 5 and 8 mass%. Measured hardness values of the composites ranged from 72 HV10 to 80 HV10. Based on the probability values (p<0.05), it was determined which factors are important for the system response. Statistical analysis has shown that linear terms of the influence factors (size and mass fraction of reinforcement particles) and the square term of the mass fraction have statistical significance on the hardness change. The square term of the particle size and the interaction term of the influencing parameters do not have a statistically significant contribution in predicting the hardness value. Thus, a second-order polynomial model was obtained by the regression analysis. Influence of input factors on the system response and the adequacy of the obtained mathematical model were determined by using the Analysis of Variance (ANOVA). Based on the statistical data analysis, it was established that, the particle mass fraction has a greater influence on hardness of the obtained composite in relation to the particle size. By comparing the experimental and predicted values, a high degree of agreement was achieved so that the chosen model of the factorial experiment was adequate (R2=0.989). It can be also concluded that the developed regression model can be applied to predict hardness of the aluminum composite reinforced by Al2O3 particles in the chosen variation interval of particle size and mass fraction.

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