This study contrasts from other AI studies on the formability with its focus on the microstructural features and not only on the experimental FLD curves. In this regard, effect of an aspect of microstructural factor, namely existence of stress-induced martensite, on the formability of the stainless sheet metals is investigated in the present study. In this sense, using artificial intelligence could be helpful. Therefore, incorporation of all microstructural factors is hardly possible in analytical methods. On the other hand, the microstructural features to be considered are numerous. 64 utilized ANFIS to observe effects of different parameters on the hole expansion process.Īs discussed briefly in the above review, effect of the microstructure on the forming limit diagrams are scarcely addressed in the literature. Indeed, several factors combines in reduction of stretchability of sheets in the case of austenitic stainless steels. They considered only phenomenological observations in the experimental tests to train a neural network on for prediction of the formability. 63 considered the effects of cold rolling on the formability of 304 L steels. Beside the phase of metals several other microstructural features arising from different processing of heat treatmetnt, cold working, aging affects the ductility, fracture, machinability, etc. In plain carbon steel no phase transformation occur in the microstructure of the metal. The mechanism of the hardening and reducing formability is different in the plain carbon steel from austenitic stainless steels. Dislocation density in low carbon steels increases extensively due to cold rolling. 45 engaged ANFIS to predict formability of plain carbon steel sheet metals under different rolling conditions. Other chemical properties also affected the nano-scale material properties as investigated in many research articles 53. 44 utilized machine learning method to optimize the chemical condition leading to producing smaller nano-silica particle. Using artificial intelligence methods in the science and engineering fields are increasing due to their versatility in modeling complex problems without engaging the physical and mathematical foundations of the problem 44, 45, 46, 47, 48, 49, 50, 51, 52. It was revealed that increase in the tensile strain increases the volume fraction of martensite fractions. Volume of strain-induced martensite under tensile loading condition in various loading rate was measured experimentally by Shen et al. It was observed that based on the temperature value, the hydrogen could results in fracture or enhancing formability of the 316 L steels. 42 explored the effects of strain-induced twinning and martensite in selective laser melted austenitic steel 316 L on the hydrogen embrittlement in a range of temperature. In the case of austenitic steels, existence of strain-induced martensite ( \(\)-martensite transformation was observed to be strain path dependent. Effect of microstructure on the formability of the stainless sheet metals is a major concern for engineers in sheet industries.
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