Artificial neural network (ANN) approach to predicting micro hardness profile values of iron-based sintered alloys

  • Desislava Yordanova Mincheva Technical university of Varna
  • Georgi Stefanov Antonov Technical University of Varna
Keywords: PM sintered compacts, sintering atmosphere, heating rate, micro hardness, artificial neural network


Recent interest in artificial neural networks has considerably extended their use in the field of powder metallurgy. Advanced in the paper is a model for predicting the micro hardness of sintered compacts made from iron powders and powder mixtures through the process of sintering performed in different atmospheres. The proposed model is based on three layer neural network with backpropagation learning algorithm. Specially developed software has been used to provide for the proper functioning of the neural network. Moreover, it should also be noted that the training data used to carry out the research has been collected by a laboratory controlled experimental testing. Finally, the paper concludes that the presented neural network model is applicable for hardness profile prediction of iron-based sintered alloys as confirmed by the experimental results.


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How to Cite
Mincheva, D., & Antonov, G. (2017, December 28). Artificial neural network (ANN) approach to predicting micro hardness profile values of iron-based sintered alloys. ANNUAL JOURNAL OF TECHNICAL UNIVERSITY OF VARNA, BULGARIA, 1(1), 1-5.
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