eISSN: 3023-3267 editor@aimjournals.com
All Journals
Submit your article

Critique Open Research & Review

Open Access Peer Review International
Open Access

Neural Network Analysis for High-Speed Machining Predictions: Unraveling Cutting and Process Parameters Correlation

DOI https://doi.org/10.55640/corr-1-1-3
PDF
Anwar Hussain 1 ,
4 M. Tech Student Department of Mechanical Engineering, Nimra College of Engineering, Andhra Pradesh, India

Abstract

In the realm of high-speed machining, achieving optimal cutting and process parameters is paramount for efficiency, precision, and tool longevity. This study employs a neural network approach to unravel the intricate correlation between cutting and process parameters, offering predictive insights that can enhance machining operations. By leveraging machine learning techniques, we explore large datasets encompassing various machining scenarios to establish patterns and relationships between cutting speeds, tool materials, feed rates, and other parameters. The resulting neural network model provides a valuable tool for engineers and manufacturers to optimize their machining processes, reduce waste, and improve productivity in high-speed machining environments.

Ā 

Keywords

High-Speed Machining, Neural Network Analysis, Machining Predictions, Cutting Parameters

References

Abukhshim NA, Mativenga PT, Sheikh MA. Heat generation and temperature prediction in metal cutting: A review and implication for high speed machining. International Journal of Machine Tools & Manufacture2006; 46:782-800.
Alavuden A, Venkateswaran N, Jeyaraj P. Manufacturing technology. Anuradha Agencies, Ed-1, 2.
Altin A, Nalbant M, Taskesen A. The effects of cutting speed on tool wear and tool life when machining Inconel718 with ceramic tools. Journal of material and design2007; 28:2518-2522.
Aslan E, Camus N, Birgoren B. Design optimization of cutting parameters when turning hardened AISI 4140 steel with Al2O3+ TiCN mixed ceramic tool. Journal of material and design 2007; 28:1618-1622.
Coelho RT, Silva LR, Braghini AJr, Bezerra AA. Some effects of cutting edge preparation and geo metric modifications when turning INCONEL 718 at high cutting speeds. Journal of Materials Processing Technology 2004;148:147-153.
Dalela S. Manufacturing science and technology. Umesh Publication, Ed-1, 2.80.
Devillez A, Schneider F, Dominiak S, Dudzinski D, Larrouquere D. Cutting forces and wear in dry machining of Inconel 718 with coated carbide tools. Journal of wear2007; 262:931-942.
John FC, Lim BS, Lennie EN. Optimal design of neural networks using the Taguchi method. Journal of neurocomputing 1995; 7:225-245.

Most read articles by the same author(s)

<< < 1 2 3 4 5 6 

Similar Articles

1-10 of 29

You may also start an advanced similarity search for this article.