Using of artificial neural network for the prediction of tribological properties of plasma nitrided 316L stainless steel

Yetim, A.F.; Çodur, Muhammed Yasin; Yazıcı, Mustafa

doi:10.1016/j.matlet.2015.06.015

Cited by 42 publications

(19 citation statements)

References 9 publications

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“…It is almost impossible to describe their highly non-linear correlation quantitatively by building a reliable equation. In recent years, the artificial neural network (ANN) technique has been proposed as a powerful tool to deal with a series of complicated problems such as non-linear systems and unknown data prediction (Ref [15][16][17][18]. Therefore, the ANN method is applicable to describe the processing parameters-impact toughness correlation of Ti-6Al-4V alloy quantitatively.…”

Section: Introductionmentioning

confidence: 99%

Study on the Hot Processing Parameters-Impact Toughness Correlation of Ti-6Al-4V Alloy

Shi

Zeng

Sun

et al. 2016

J. of Materi Eng and Perform

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In this research, the hot processing parameters-impact toughness correlation of Ti-6Al-4V titanium alloy is studied. Fifty-four groups of hot processing treatments with different forging temperatures (930, 950, 970°C), deformation degrees (20, 50, 80%), annealing temperatures (600, 700, 800°C), and annealing time (1 and 5 h) were conducted. The orthogonal design was used to find the primary hot processing parameters influencing the impact toughness of Ti-6Al-4V alloy. The results show that the annealing temperature can exert the biggest influence on impact toughness. Low annealing temperature is essential to achieve high impact toughness value. In addition, the BP neural network was used to describe the quantitative correlation between hot processing parameters and impact toughness. The results show that the BP neural network exhibits good performance in predicting the impact toughness of Ti-6Al-4V alloy. The prediction error is within 5%. The BP neural network and the orthogonal design method are mutually confirmed in the present work. Finally, based on the microstructure analysis, the reasons responsible for above experimental results are explained.

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Section: Introductionmentioning

confidence: 99%

Study on the Hot Processing Parameters-Impact Toughness Correlation of Ti-6Al-4V Alloy

Shi

Zeng

Sun

et al. 2016

J. of Materi Eng and Perform

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“…Kumar et al used the method of ANN in order to anticipate the loss of Sintered Cu-SiC composited due to abrasive wear [121]. Yetim et al used ANN to predict the properties of wear in plasma nitriding, and in the paper it is concluded that ANN prediction was similar to the results obtained after doing the experiment [122].…”

Section: Tribotronic Systemmentioning

confidence: 97%

A Review on Tribological Wear Test Rigs for Various Applications

bawab

Nirmal

Isa

et al. 2018

IJIE

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To mimic a tribosystem setup to the real time model while taking into consideration the subject of green tribology, many tribological wear test rigs are invented. The current work is a dedicated review on the latest development of various tribological wear test rigs build for numerous applications. With the aid of diagrams, the working principles of the machines which are built on specific standards are discussed. Their operating parameters associated with related research using these machines are also included. In addition, recommendations and directions for improvements in tribology machines are reported.

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“…The ANN model is nevertheless trustworthy for the minimal error rate of the output results (Shuvho et al , 2019a, 2019b). The material wear can be predicted with ANN models successfully (Sahu et al , 2010; Yetim et al , 2015).…”

Section: Introductionmentioning

confidence: 99%

Tribo-performance analysis of HVOF sprayed 86WC-10Co4Cr & Ni-Cr₂O₃ on AISI 316L steel using DOE-ANN methodology

Singh

2021

ILT

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Purpose The purpose of this paper is to carry out erosion wear investigation on high-velocity oxy-fuel (HVOF)-deposited 86WC-10Co4Cr and synergistic Ni/Chromia powder (i.e. 80Ni-20Cr2O3) on AISI 316L. Design/methodology/approach Design of experiments-artificial neural network (DOE-ANN) methodology was adopted to calculate the erosion wear. Taguchi’s orthogonal array L16 (42) was used to perform set-of-erosion experiments followed by lower-the-better rule. The artificial neural network (ANN) model is used on erosion wear data obtained from the experiments. Findings Experimental results indicate that 86WC-10Co4Cr provided better erosion wear resistance as compared to Ni/Chromia. The erosion wear of 86WC-10Co4Cr and synergistic Ni/Chromia coatings increases with an increase in time duration, solid concentration and time. The magnitude of erosion generated by ashes was comparatively lower than sand. The arithmetic mean roughness (Ra) of finished AISI 316L, 86WC-10Co4Cr and Ni/Chromia coating was found as 0.46 ± 0.13, 6.50 ± 0.16 and 7.04 ± 0.23 µm, respectively. Surface microhardness of AISI 316L, 86WC-10Co4Cr and Ni/Chromia coating was found as 197 ± 18, 1,156 ± 18 and 1,021± 21 HV, respectively. Practical implications The present results can be useful for estimation of erosion wear in slurry pumps used in mining industry for the conveying of sand and in thermal power plants for the conveying of ashes to the dyke area. Originality/value The erosion wear of HVOF-sprayed 86WC-10Co4Cr and Synergistic Ni/Chromia powders was studied experimentally as well as predicted by the ANN model, and wear mechanisms are well discussed by scanning electron micrographs.

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Using of artificial neural network for the prediction of tribological properties of plasma nitrided 316L stainless steel

Cited by 42 publications

References 9 publications

Study on the Hot Processing Parameters-Impact Toughness Correlation of Ti-6Al-4V Alloy

Study on the Hot Processing Parameters-Impact Toughness Correlation of Ti-6Al-4V Alloy

A Review on Tribological Wear Test Rigs for Various Applications

Tribo-performance analysis of HVOF sprayed 86WC-10Co4Cr & Ni-Cr₂O₃ on AISI 316L steel using DOE-ANN methodology

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Using of artificial neural network for the prediction of tribological properties of plasma nitrided 316L stainless steel

Cited by 42 publications

References 9 publications

Study on the Hot Processing Parameters-Impact Toughness Correlation of Ti-6Al-4V Alloy

Study on the Hot Processing Parameters-Impact Toughness Correlation of Ti-6Al-4V Alloy

A Review on Tribological Wear Test Rigs for Various Applications

Tribo-performance analysis of HVOF sprayed 86WC-10Co4Cr & Ni-Cr2O3 on AISI 316L steel using DOE-ANN methodology

Contact Info

Product

Resources

About

Tribo-performance analysis of HVOF sprayed 86WC-10Co4Cr & Ni-Cr₂O₃ on AISI 316L steel using DOE-ANN methodology