The Use of Fuzzy Systems for Forecasting the Hardenability of Steel

Sitek, W.; Irla, A.

doi:10.1515/amm-2016-0134

Cited by 7 publications

(4 citation statements)

References 27 publications

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“…a quasi-sigmoidal monotonic decreasing function) and wavelet NNs are applied to correlate the steel chemistry to the function parameters. Quite recently also fuzzy systems have been applied for the determination of the Jominy hardenability curve based on the chemical composition, although the investigation was limited to structural steels for quenching and tempering [38].…”

Section: Data-driven Approaches To Forecast Steel Hardenabilitymentioning

confidence: 99%

Automatic steel grades design for Jominy profile achievement through neural networks and genetic algorithms

Vannucci

Colla

2021

Neural Comput & Applic

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The paper proposes an approach to the design of the chemical composition of steel, which is based on neural networks and genetic algorithms and aims at achieving a desired hardenability behavior possibly matching other constraints related to the steel production. Hardenability is a mechanical feature of steel, which is extremely relevant for a wide range of steel applications and refers to the steel capability to improve its hardness following a heat treatment. In the proposed approach, a neural-network-based predictor of the so-called Jominy hardenability profile is exploited, and an optimization problem is formulated, where the optimization function allows taking into account both the desired accuracy in meeting the target Jominy profile and other constraint. The optimization is performed through genetic algorithms. Numerical results are presented and discussed, showing the efficiency of the proposed approach together with its flexibility and easy customization with respect to the user demands and production objectives.

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Section: Data-driven Approaches To Forecast Steel Hardenabilitymentioning

confidence: 99%

Automatic steel grades design for Jominy profile achievement through neural networks and genetic algorithms

Vannucci

Colla

2021

Neural Comput & Applic

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“…Recently, fuzzy systems were also adopted to estimate the Jominy profile using the steel metallurgy, [ 39 ] but the research work focused on structural steels for quenching and tempering.…”

Section: Introductionmentioning

confidence: 99%

A Deep Learning‐Based Approach to the Estimation of Jominy Profile of Medium‐Carbon Quench Hardenable Steels

Colla,

Vannucci,

Matino

et al. 2023

steel research int.

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The possibility to estimate the Jominy profile of steel based on its chemical composition is of utmost importance and high practical relevance for industries, at enables a preliminary assessment of the suitability of a specific steel grade to a particular application or to the requirements of a customer, by saving time and resources as the Jominy end‐quench test is costly and time consuming. More importantly, an estimator can be used in steel grade design, by supporting the investigation of the most suitable chemistry to meet some given specifications. The paper proposes a novel approach to estimate the hardenability profile of medium Carbon quench hardenable steels, which exploits the potential of deep learning to correlate the steel metallurgy to the entire shape of the curve rather than to its single points, by thus being adaptable to a wide range of steel grades while providing very accurate estimates. Moreover, the proposed approach is suitable implement a transfer learning paradigm, as it can exploit the knowledge acquired by training on a specific dataset to adapt the model to different steel grades for which less data or data holding different features are available.This article is protected by copyright. All rights reserved.

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“…Hardenability models proposed in the literature [5,[14][15][16][17][18][19][20][21] do not show the full relevance to the experimental data, probably due to incomplete verification, too small or even unrepresentative set of experimental data. Full adequacy of the mathematical model can be performed on a large number of melts with appropriately selected and exactly controlled chemical compositions exhausting all possible combinations of alloying elements present in the steel group [22][23][24][25]. This creates the necessity of seeking a new model-modern tools and computational methods, including artificial neural networks indicate the chances of solving this problem [26][27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Modelling and Analysis of the Synergistic Alloying Elements Effect on Hardenability of Steel

Sitek,

Trzaska,

Gemechu

2022

Archives of Foundry Engineering

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The paper presents a methodology of modeling relationships between chemical composition and hardenability of structural alloy steels using computational intelligence methods, that are artificial neural network and multiple regression models. Particularly, the researchers used unidirectional multilayer teaching method based on the error backpropagation algorithm and a quasi-newton methods. Based on previously known methodologies, it was found that there is no universal method of modeling hardenability, and it was also noted that there are errors related to the calculation of the curve. The study was performed on large set of experimental data containing required information on about the chemical compositions and corresponding Jominy hardenability curves for over 400 data steel heats with variety of chemical compositions. It is demonstrated that the full practical usefulness of the developed models in the selection of materials for particular applications with intended performance in the area of application.

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The Use of Fuzzy Systems for Forecasting the Hardenability of Steel

Cited by 7 publications

References 27 publications

Automatic steel grades design for Jominy profile achievement through neural networks and genetic algorithms

Automatic steel grades design for Jominy profile achievement through neural networks and genetic algorithms

A Deep Learning‐Based Approach to the Estimation of Jominy Profile of Medium‐Carbon Quench Hardenable Steels

Modelling and Analysis of the Synergistic Alloying Elements Effect on Hardenability of Steel

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