Mechanical behavior of powder metallurgy steel - Experimental investigation and artificial neural network-based prediction model

Mechanical properties of high-density powder metallurgy (PM) steels have been evaluated using standard tests, and a theoretical model using the artificial neural network (ANN) has been developed. Various heat treatments mere carried out to study their influence on mechanical properties, viz. endurance limit (EL), yield strength (YS), and hardness, and also on the carbon content in PM steel. The material containing 0.47% C that was quenched and tempered at 503 K (QT 503 K) showed the optimum combination of yield strength/ultimate tensile strength (YS/UTS) and EL. The ANN-based model showed excellent agreement with experimental results. Prediction models based on the ANN are demonstrated for YS as well as for the EL as a function of heat treatment (ranging from QT 400 K to QT 900 K) and percent carbon (%C) (between 0.1 and 0.5). This mould help the materials engineer suitably design the heat-treatment schedule to obtain the desired/best combination of fatigue and strength properties.