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In this paper, a computational method to predict the corrosion resistance of some sintered iron alloys subjected to a thermochemical treatment is analyzed. The proposed materials are obtained by powder metallurgy (P/M) route. The raw materials are prepared from atomized pre-alloyed iron base powders. The compacted samples were obtained by cold pressing using conventional route. The powders were compacted at a pressures of 400 and 600 MPa. After pressing, the green compacts were sintered in a laboratory furnace. Th...

Application of image processing recognition in the agricultural field is a difficult and intensive task. Recent years developments of technologies such as GPUs (Graphics Processing Units) and the fast development of artificial intelligence algorithms allows the reliability of using computer vision technology to be used for recognition of plants, including weeds, ensuring the efficiency of intelligent agricultural systems. Computer vision technology uses a camera and a computer to identify and measure objects in th...

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. T...

Modeling using artificial neural networks (ANNs) is used in most fields of production. An approach to modeling the dimensional changes in some iron-based powder metallurgy (PM) parts during the sintering process is given. The proposed model used is a multilayer neural network with a backpropagation learning algorithm. This type of neural network model gave the best results in the process of modeling. The specimens used in this study are prealloyed iron-based powders. The particle size of the powders is ranging fro...

The purpose of this paper was to study the effect of carbon content on the dimensional characteristics of some powder metallurgy (PM) materials. The powders used in this study are atomized pure iron and prealloyed iron-based powders with Cu, Ni and Mo. Some elements as copper, nickel, molybdenum, manganese and phosphorus are the most common alloying element added in powders form because of its low cost, availability and capability to improve the properties of alloys. The particle size of the analyzed powders is ra...

The objective of the study was to evaluate the effect of processing parameters such as pressing and sintering time on microstructural characteristics including porosity and microstructure of some iron-based powder metallurgy (PM) materials. The powders used in this study are prealloyed iron-based powders. The particle size of the powders is ranging from 45 to 150 ?m. Following mixing the powders with zinc stearate 1% for 30 minutes, the studied powders were single pressed in a die at a pressure of 600 MPa. Zn-stea...

A learning algorithm was used as an artificial neural network (ANN) tool to predict the mechanical properties of some iron-based powder metallurgy (P/M) materials. Specimens prepared from atomized iron powder and from pre-alloyed iron base powders powders were analyzed in this paper. The specimens were fabricated by press and sintering of the mixed powders. The samples were compressed in a universal mechanical testing machine to a pressure of 400 and 600 MPa. The sintering temperature was approximately 1.150 пїЅC....