Cargando…

Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach

The critical applications of difficult-to-machine Inconel 617 (IN617) compel the process to be accurate enough that the requirement of tight tolerances can be met. Electric discharge machining (EDM) is commonly engaged in its machining. However, the intrinsic issue of over/undercut in EDM complicate...

Descripción completa

Detalles Bibliográficos
Autores principales: Ishfaq, Kashif, Sana, Muhammad, Waseem, Muhammad Umair, Ashraf, Waqar Muhammad, Anwar, Saqib, Krzywanski, Jaroslaw
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10456530/
https://www.ncbi.nlm.nih.gov/pubmed/37630072
http://dx.doi.org/10.3390/mi14081536
_version_ 1785096721621057536
author Ishfaq, Kashif
Sana, Muhammad
Waseem, Muhammad Umair
Ashraf, Waqar Muhammad
Anwar, Saqib
Krzywanski, Jaroslaw
author_facet Ishfaq, Kashif
Sana, Muhammad
Waseem, Muhammad Umair
Ashraf, Waqar Muhammad
Anwar, Saqib
Krzywanski, Jaroslaw
author_sort Ishfaq, Kashif
collection PubMed
description The critical applications of difficult-to-machine Inconel 617 (IN617) compel the process to be accurate enough that the requirement of tight tolerances can be met. Electric discharge machining (EDM) is commonly engaged in its machining. However, the intrinsic issue of over/undercut in EDM complicates the achievement of accurately machined profiles. Therefore, the proficiency of deep cryogenically treated (DCT) copper (Cu) and brass electrodes under modified dielectrics has been thoroughly investigated to address the issue. A complete factorial design was implemented to machine a 300 μm deep impression on IN617. The machining ability of DCT electrodes averagely gave better dimensional accuracy as compared to non-DCT electrodes by 13.5% in various modified dielectric mediums. The performance of DCT brass is 29.7% better overall compared to the average value of overcut (OC) given by DCT electrodes. Among the non-treated (NT) electrodes, the performance of Cu stands out when employing a Kerosene-Span-20 modified dielectric. In comparison to Kerosene-Tween-80, the value of OC is 33.3% less if Kerosene-Span-20 is used as a dielectric against the aforementioned NT electrode. Finally, OC’s nonlinear and complex phenomena are effectively modeled by an artificial neural network (ANN) with good prediction accuracy, thereby eliminating the need for experiments.
format Online
Article
Text
id pubmed-10456530
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-104565302023-08-26 Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach Ishfaq, Kashif Sana, Muhammad Waseem, Muhammad Umair Ashraf, Waqar Muhammad Anwar, Saqib Krzywanski, Jaroslaw Micromachines (Basel) Article The critical applications of difficult-to-machine Inconel 617 (IN617) compel the process to be accurate enough that the requirement of tight tolerances can be met. Electric discharge machining (EDM) is commonly engaged in its machining. However, the intrinsic issue of over/undercut in EDM complicates the achievement of accurately machined profiles. Therefore, the proficiency of deep cryogenically treated (DCT) copper (Cu) and brass electrodes under modified dielectrics has been thoroughly investigated to address the issue. A complete factorial design was implemented to machine a 300 μm deep impression on IN617. The machining ability of DCT electrodes averagely gave better dimensional accuracy as compared to non-DCT electrodes by 13.5% in various modified dielectric mediums. The performance of DCT brass is 29.7% better overall compared to the average value of overcut (OC) given by DCT electrodes. Among the non-treated (NT) electrodes, the performance of Cu stands out when employing a Kerosene-Span-20 modified dielectric. In comparison to Kerosene-Tween-80, the value of OC is 33.3% less if Kerosene-Span-20 is used as a dielectric against the aforementioned NT electrode. Finally, OC’s nonlinear and complex phenomena are effectively modeled by an artificial neural network (ANN) with good prediction accuracy, thereby eliminating the need for experiments. MDPI 2023-07-31 /pmc/articles/PMC10456530/ /pubmed/37630072 http://dx.doi.org/10.3390/mi14081536 Text en © 2023 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
Ishfaq, Kashif
Sana, Muhammad
Waseem, Muhammad Umair
Ashraf, Waqar Muhammad
Anwar, Saqib
Krzywanski, Jaroslaw
Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach
title Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach
title_full Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach
title_fullStr Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach
title_full_unstemmed Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach
title_short Enhancing EDM Machining Precision through Deep Cryogenically Treated Electrodes and ANN Modelling Approach
title_sort enhancing edm machining precision through deep cryogenically treated electrodes and ann modelling approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10456530/
https://www.ncbi.nlm.nih.gov/pubmed/37630072
http://dx.doi.org/10.3390/mi14081536
work_keys_str_mv AT ishfaqkashif enhancingedmmachiningprecisionthroughdeepcryogenicallytreatedelectrodesandannmodellingapproach
AT sanamuhammad enhancingedmmachiningprecisionthroughdeepcryogenicallytreatedelectrodesandannmodellingapproach
AT waseemmuhammadumair enhancingedmmachiningprecisionthroughdeepcryogenicallytreatedelectrodesandannmodellingapproach
AT ashrafwaqarmuhammad enhancingedmmachiningprecisionthroughdeepcryogenicallytreatedelectrodesandannmodellingapproach
AT anwarsaqib enhancingedmmachiningprecisionthroughdeepcryogenicallytreatedelectrodesandannmodellingapproach
AT krzywanskijaroslaw enhancingedmmachiningprecisionthroughdeepcryogenicallytreatedelectrodesandannmodellingapproach