In this paper, enhancing the tribological characteristics of novel cast metallic materials—hybrid multi-component cast irons—by applying a strengthening heat treatment is described. The experimental materials were the cast alloys of a nominal composition (5 wt.% W, 5 wt.% Mo, 5 wt.% V, 10 wt.% Cr, 2.5 wt.% Ti, Fe is a balance) supplemented with 0.3–1.1 wt.% C and 1.5–2.5 wt.% B (total of nine alloys). The heat treatment was oil-quenching followed by 200 °C tempering. The quench temperature (QT) varied in the range of 900–1200 °C, with a step of 50 °C (with a 2-h holding at QT). The correlation of the QT with microstructure and properties was estimated using microstructure/worn surface characterization, differential scanning calorimetry, hardness measurement, and three-body-abrasive wear testing (using Al2O3 particles). The as-cast alloys had a multi-phase structure consisting of primary and/or eutectic borocarbide M2(B,C)5, carboborides M(C,B), M7(C,B)3, M3(C,B), and the matrix (ferrite, martensite, pearlite/bainite) in different combinations and volume fractions. Generally, the increase in the quenching temperature resulted in a gradual increase in hardness (maximally to 66–67 HRC) and a decrease in the wear rate in most alloys. This was due to the change in the phase-structure state of the alloys under quenching, namely, the secondary carboboride precipitation, and replacing ferrite and pearlite/bainite with martensite. The wear rate was found to be inversely proportional to bulk hardness. The maximum wear resistance was attributed to QT = 1150–1200 °C, when the wear rate of the alloys was lowered by three to six times as compared to the as-cast state. With the QT increase, the difference in the wear rate of the alloys decreased by three times. The highest abrasive resistance was attributed to the alloys with 1.1 wt.% C, which had a 2.36–3.20 times lower wear rate as compared with that of the reference alloy (13 wt.% Cr cast iron, hardness of 66 HRC). The effects of carbon and boron on hardness and wear behavior are analyzed using the regression models developed according to the factorial design procedure. The wear mechanisms are discussed based on worn surface characterization.
