Scholarly record
ARTIFICIAL NEURAL NETWORK (ANN) APPLICATION TO PREDICT THE MECHANICAL PROPERTIES IN SOME IRON-BASED POWDER METALLURGY ALLOYS
Abstract
In the present study, the mechanical properties of some iron-based sintered alloys prepared by powder metallurgy route were predicted using Artificial Neural Network (ANN) approach. Artificial Neural Networks (ANNs) are important tools used to predict the complex processes with many variables and interactions. In order to prepare the sintered compacts, the powders prepared from pre-alloyed iron base powders produced by atomization (< 45, 45-63, 63-100, 100-150, >150 ?m) were the materials analyzed in this paper. The analyzed powders were consolidated in compacts in a mold using uniaxial pressing at 400 and 600 MPa with the disc dimensions of ? 8 ? 6 mm. Then, the consolidated compacts of prepared powders were sintered in a laboratory furnace at two different temperatures. The sintering temperature was approximately 1.150°C and two sintering times of 60 and 90 minutes. The microhardness measurements were performed to evaluate the mechanical properties of these specimens. Then, to predict the mechanical properties of the sintered specimens, a neural network as multi layer perceptron back propagation type was constructed. It was found that the proposed ANN model studied in this paper can be used as an alternative to predict the mechanical properties of some iron-based materials obtained by powder metallurgy route.
Publication Impact Profile
Publication details
References15
Reihanian M., Asadullahpour S. R., Hajarpour S., Gheisari Kh., Application of neural network and genetic algorithm to powder metallurgy of pure iron, Materials and Design, vol. 32, issue 6, pp. 3183-3188, 2011.
Allison P. G., Hammi Y., Jordon J. B., Horstemeyer M. F., Modelling and experimental study of fatigue of powder metal steel (FC-0205), Powder Metallurgy, vol. 56:5, pp. 388-396, 2013.
Iacoviello F., Iacoviello D., Cavallini M., Analysis of stress ratio effects on fatigue propagation in a sintered duplex steel by experimentation and artificial neural network approaches, vol. 26 , pp. 819-828, 2004.
Vettivel S. C., Selvakumar N., Leema N., Experimental and prediction of sintered Cu–W composite by using artificial neural networks, Materials & Design, vol. 45, pp. 323-335, 2013;
Marin M, Potecasu F, Marin F., Potecasu O, Alexandru P., Prediction of porosity in iron-based powder metallurgy (P/M) materials using an image processing software, 16th International Multidisciplinary Scientific Geoconference (SGEM 2016), Conference Proceedings, vol. I, pp. 259-264, 2016.
Bhadeshia H. K. D. H., Neural Networks in Materials Science, ISIJ International, vol. 39, no. 10, pp, 966-979; 1999;
Xia X., Nie J. F., Davies C.H.J., Tang W.N., Xu S.W., Birbilis N. , An artificial neural network for predicting corrosion rate and hardness of magnesium alloys, Materials & Design, vol. 90, pp. 1034-1043, 2016.
Verpoort P.C., MacDonald P., Conduit G.J., Materials data validation and imputation with an artificial neural network Computational Materials Science, vol. 147, pp. 176-185, 2018.
Gething B.A., Heaney D.F., Koss D.A., Mueller T.J, The effect of nickel on the mechanical behavior of molybdenum P/M steels, Materials Science and Engineering A, vol. 390, pp. 19–26, 2005.
Bourcier R., Koss D., Smelser R., Richmond O., The influence of porosity on the fracture of alloys, Acta Metall, vol. 34, p. 2443–53, 1983.
Christian K., German R., Relation between pore structure and fatigue behavior in sintered iron-copper-carbon, Int J Powder Metall, vol. 31, p. 51– 61, 1995.
Gurau C., Gurau G., Sampath V., Structural study and phase transformation of Cu-Al-Ni shape memory alloy produced by severe plastic deformation, Indian journal of engineering and materials sciences, volume: 25, issue 1, pp. 5-10, 2018.
Haynes R., A study of effect of porosity content on ductility of sintered metals, Powder Metall, vol. 20, pp. 17–20, 1997.
Chagnon F., Trudel Y., Effect of sintering parameters on mechanical properties of sinter hardened materials, Advances in P/M & Particulate Materials, NJ, vol.2, pp 14-97/14-106, 1997.
Piotrowski A., Biallas G., Influence of sintering temperature on pore morphology, Microstructure and Fatigue Behavior of Mo-Ni-Cu Alloyed Sintered Steel, Powder Metallurgy, vol.41, no.2, pp.109-114, 1998.
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.
