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Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods

Precise machining of micro parts from difficult-to-cut materials requires using advanced technology such as wire electrical discharge machining (WEDM). In order to enhance the productivity of micro WEDM, the key role is understanding the influence of process parameters on the surface topography and...

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Autores principales: Oniszczuk-Świercz, Dorota, Świercz, Rafał, Michna, Štefan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737947/
https://www.ncbi.nlm.nih.gov/pubmed/36499841
http://dx.doi.org/10.3390/ma15238317
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author Oniszczuk-Świercz, Dorota
Świercz, Rafał
Michna, Štefan
author_facet Oniszczuk-Świercz, Dorota
Świercz, Rafał
Michna, Štefan
author_sort Oniszczuk-Świercz, Dorota
collection PubMed
description Precise machining of micro parts from difficult-to-cut materials requires using advanced technology such as wire electrical discharge machining (WEDM). In order to enhance the productivity of micro WEDM, the key role is understanding the influence of process parameters on the surface topography and the material’s removal rate (MRR). Furthermore, effective models which allow us to predict the influence of the parameters of micro-WEDM on the qualitative effects of the process are required. This paper influences the discharge energy, time interval, and wire speed on the surface topography’s properties, namely Sa, Sk, Spk, Svk, and MRR, after micro-WEDM of Inconel 718 were described. Developed RSM and ANN model of the micro-WEDM process, showing that the discharge energy had the main influence (over 70%) on the surface topography’s parameters. However, for MRR, the time interval was also significant. Furthermore, a reduction in wire speed can lead to a decrease in the cost process and have a positive influence on the environment and sustainability of the process. Evaluation of developed prediction models of micro-WEDM of Inconel 718 indicates that ANN had a lower value for the relative error compared with the RSM models and did not exceed 4%.
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spelling pubmed-97379472022-12-11 Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods Oniszczuk-Świercz, Dorota Świercz, Rafał Michna, Štefan Materials (Basel) Article Precise machining of micro parts from difficult-to-cut materials requires using advanced technology such as wire electrical discharge machining (WEDM). In order to enhance the productivity of micro WEDM, the key role is understanding the influence of process parameters on the surface topography and the material’s removal rate (MRR). Furthermore, effective models which allow us to predict the influence of the parameters of micro-WEDM on the qualitative effects of the process are required. This paper influences the discharge energy, time interval, and wire speed on the surface topography’s properties, namely Sa, Sk, Spk, Svk, and MRR, after micro-WEDM of Inconel 718 were described. Developed RSM and ANN model of the micro-WEDM process, showing that the discharge energy had the main influence (over 70%) on the surface topography’s parameters. However, for MRR, the time interval was also significant. Furthermore, a reduction in wire speed can lead to a decrease in the cost process and have a positive influence on the environment and sustainability of the process. Evaluation of developed prediction models of micro-WEDM of Inconel 718 indicates that ANN had a lower value for the relative error compared with the RSM models and did not exceed 4%. MDPI 2022-11-23 /pmc/articles/PMC9737947/ /pubmed/36499841 http://dx.doi.org/10.3390/ma15238317 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Oniszczuk-Świercz, Dorota
Świercz, Rafał
Michna, Štefan
Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods
title Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods
title_full Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods
title_fullStr Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods
title_full_unstemmed Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods
title_short Evaluation of Prediction Models of the Microwire EDM Process of Inconel 718 Using ANN and RSM Methods
title_sort evaluation of prediction models of the microwire edm process of inconel 718 using ann and rsm methods
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9737947/
https://www.ncbi.nlm.nih.gov/pubmed/36499841
http://dx.doi.org/10.3390/ma15238317
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