Using of artificial neural network for the prediction of tribological properties of plasma nitrided 316L stainless steel

• 316L stainless steel samples were nitrided at different process temperatures to obtain s-phase.
• Structural, artificial neural network and wear properties were investigated.
• It was observed that nitriding at low temperatures was necessary to form s-phase in the modified layer.

In the present study, wear rate of the 316L stainless steel was predicted by using artificial neural network (ANN). The influence of plasma nitriding on mechanical and tribological properties of 316L stainless steels were investigated using X-ray diffraction, microhardness tester, scanning electron microscopy and pin-on-disk tribotester. Plasma nitriding treatments were performed for 1, 4 and 8 h in 50% H2–50% N2 gas mixture, at the temperatures of 350, 375, 400, 425, 450 and 500 °C. The results show that CrN and γ'-Fe4N phases were observed at the higher temperatures than 400 °C while s-phase formed at the temperatures under 400 °C, Also, modeling results showed that the wear rate of the 316L stainless steel was predicted with high accuracy by ANN.