Optimization and analysis of dry sliding wear behaviour of N-B4C/MOS2 unreinforced AA2219 nano hybrid composites using response surface methodology

The effect of heat treatment on nano-size B4C particle reinforced hybrid composites is discussed in this paper. For this, AA2219 with 2% by weight nano and MoS2 particulates were fabricated using a two-stage stir casting process, the specimens treated to assess their influence wear behavior. Experiments carried out study behavior varying important factors such as aging temperature, load, sliding distance. Response Surface Methodology (RSM) designed Box-Behnken was used identify critical variables influencing rate optimize To comprehend mechanisms involved, an analysis worn surface presented. Based analysis, regression equation predictability 97.2% developed for response obtain optimum rate. following order effectively captures relative importance various determining alloy's resistance: distance, temperature. When compared load treatments via artificial temperature range 200-240 °C have no significant resistance n-B4C particulates. However, when considered, exhibit better at 240 ice quenching.