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

• Published in: International journal on interactive design and manufacturing Vol. 18; no. 1; pp. 119 - 131
• Main Authors: Shrivastava, Ekta, Shrivastava, Pankaj Kumar, Singh, Pushpendra, Gautam, Subhash, Singh, Abhijeet
• Format: Journal Article
• Language: English
• Published: Paris Springer Paris 01.01.2024
• Subjects: CAE) and Design; Computer-Aided Engineering (CAD; Electronics and Microelectronics; Engineering; Engineering Design; Industrial Design; Instrumentation; Mechanical Engineering; Original Paper; Artificial neural network; Modeling; Arc machining; Rao’s metaphor-less algorithms; Optimization
• ISSN: 1955-2513; 1955-2505
• DOI: 10.1007/s12008-023-01399-1

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.