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Erschienen in: International Journal on Interactive Design and Manufacturing (IJIDeM) 1/2024

08.07.2023 | Original Paper

AI based modeling & optimization of arc machining of Ti–6Al–4V alloy using ANN-evolutionary algorithm

verfasst von: Ekta Shrivastava, Pankaj Kumar Shrivastava, Pushpendra Singh, Subhash Gautam, Abhijeet Singh

Erschienen in: International Journal on Interactive Design and Manufacturing (IJIDeM) | Ausgabe 1/2024

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Abstract

Many advanced materials have been developed to fulfill the need of the present industrial paradigm. To machine these advanced materials researchers have developed many innovative processes known as unconventional machining processes (UMPs). Arc machining (AM) is one of the UMP, which is under exploration stage. In the present research a variant of AM has been developed by providing vibration to the tool electrode. The Ti–6Al–4 V alloy has been machined by using developed AM setup to evaluate important performance parameters. It has been reported that the maximum material removal rate obtained is around 2.8 g/min which is approximately 60 times more than that obtained by using conventional machining processes for Titanium alloy. The predictive models have been developed by using tool of artificial intelligence and then process optimization was done by using four different evolutionary optimization techniques namely Rao-1, Rao-2, Rao-3 and differential evolution. Rao-3 algorithm has proven to be best amongst all for current machining environment.

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Metadaten
Titel
AI based modeling & optimization of arc machining of Ti–6Al–4V alloy using ANN-evolutionary algorithm
verfasst von
Ekta Shrivastava
Pankaj Kumar Shrivastava
Pushpendra Singh
Subhash Gautam
Abhijeet Singh
Publikationsdatum
08.07.2023
Verlag
Springer Paris
Erschienen in
International Journal on Interactive Design and Manufacturing (IJIDeM) / Ausgabe 1/2024
Print ISSN: 1955-2513
Elektronische ISSN: 1955-2505
DOI
https://doi.org/10.1007/s12008-023-01399-1

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