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Special Issue "Application of Neural Networks in Processing of Metallic Materials"
A special issue of Metals (ISSN 2075-4701). This special issue belongs to the section "Metal Casting, Forming and Heat Treatment".
Deadline for manuscript submissions: 31 March 2023 | Viewed by 5566
Special Issue Editor
Interests: processing of metallic materials; metallurgy; microstructure; neural networks; artificial intelligence; process chains; quality of products; energy consumption; sustainable metal production; blockchain technology
Special Issue Information
The processing of metallic materials is one of the most demanding and expensive processes, as it requires several intermediate stages (i.e., molten metal or raw material; casting and solidification; hot, warm and/or cold working; shaping of products; heat and surface treatment), and involves high energy consumption. For this reason, it is desirable to optimise the production process (process chain) in terms of energy, mechanical properties, specific product properties, and technological yield. This can be achieved with a better and deeper understanding of the influence of process parameters, the chemical composition, as well as the production equipment used on the final properties of the products. Thus, the properties of the products are related to the technological path of the material in the production process, the chemical composition of the materials used, the production equipment used, etc. Physical phenomena that take place in materials during their production have a very complex and highly nonlinear dependence on the technological parameters that influence the evolution of the microstructure and determine its final properties. The main reason for the complexity is the multiscale nature of metal processing, which makes it difficult to develop reliable and sufficiently accurate physical models for metal material processing simulations that are also computationally undemanding to be potentially used for the on-line control of production. On the other hand, phenomenological models have many other deficiencies. However, recent advances in AI—especially in the field of modern artificial neural networks—allow the development of efficient models that can optimize production (efficient use of energy, lower production costs, improvement of desired mechanical properties, etc.).
To get closer to a greener and sustainable future of metal processing, an efficient approach is necessary. Therefore, the purpose of this Special Issue is to present works dealing with the development of novel approaches—primarily the development and application of artificial neural networks in various metal processing operations (i.e., molten metal processing, raw material processing, preparing of initial material before the deformation process, casting and solidification shaping of product and semi-product, hot and/or cold working, heat and surface treatment, etc.). However, the sharing of research results in metal processing by applying other novel approaches related to artificial intelligence and/or disruptive technologies such as IoT (Internet of Things) and/or blockchain technology is also welcome. The latter can help in controlling work processes and ensuring the immutability of process parameters.
Dr. Iztok Peruš
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metals is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- processing of metallic materials
- neural networks
- artificial intelligence
- process chains
- quality of products
- energy consumption
- sustainable metal production
- blockchain technology
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Title: Diversity of influences of chemical composition in relation to process parameters on mechanical properties for hot extruded AA 6082
Authors: S. Malej1； M.Terčelj1； I. Peruš2 and G. Kugler1
Affiliation: 1Faculty of Natural Sciences and Engineering, University of Ljubljana, Slovenia 2Faculty of Civil Engineering, Transportation Engineering and Architecture, University of Maribor, Slovenia
Title: Application of artificial intelligence for analysis of steelmaking parameters on the defects in continuously cast slabs
Authors: Matjaž Knap1, Neža Flisek1 and Boštjan Bradaškja2
Affiliation: 1Faculty of Natural Sciences and Engineering, University of Ljubljana, Slovenia 2SIJ Acroni d. o. o., Slovenia
Title: Prediction of nonmetallic inclusions in rolled pieces based on melt samples for 20MNV6 EXEM steel
Authors: Matjaž Knap1, Brina Fir2 and Nejc Drofelnik2
Affiliation: 1Faculty of Natural Sciences and Engineering, University of Ljubljana, Slovenia 2Štore Steel d.o.o.