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ANN Model Based Calculation of Tensile of Friction Surfaced Tool Steel

Authors: V. Pitchi Raju;

ANN Model Based Calculation of Tensile of Friction Surfaced Tool Steel

Abstract

Friction surface treatment is well established solid technology and is used for deposition, abrasion and corrosion protection coatings on rigid materials. This novel process has wide range of industrial applications, particularly in the field of reclamation and repair of damaged and worn engineering components. In this paper, present the prediction of tensile of friction surface treated tool steel using ANN for simulated results of friction surface treatment. This experiment was carried out to obtain tool steel coatings of low carbon steel parts by changing input process parameters such as friction pressure, rotational speed and welding speed. The simulation is performed by a 33 factor design that takes into account the maximum and minimum limits of the experimental work performed by the 23 factor design. Neural network structures, such as the Feed Forward Neural Network FFNN , were used to predict tensile tool steel sediments caused by friction. V. Pitchi Raju "ANN Model Based Calculation of Tensile of Friction Surfaced Tool Steel" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6 , October 2019, URL: https://www.ijtsrd.com/papers/ijtsrd29169.pdf

Keywords

Friction surfacing, Mechanical Engineering, Artificial Neural Networks (ANN), FOS: Mechanical engineering, Process Parameters

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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