Ensemble Machine learning based performance prediction of electrical discharge machining for AISI D6 tool steel-Reference-Cited by-同舟云学术

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Ensemble Machine learning based performance prediction of electrical discharge machining for AISI D6 tool steel

Published:2022 Issue: Volume:69 Page:720-724
ISSN:2214-7853
Container-title:Materials Today: Proceedings
language:en
Short-container-title:Materials Today: Proceedings

Author:

Matheswaran P.,Nandhini R.,Sasikumar R.,Mathumathi M.

Publisher

Elsevier BV

Subject

General Medicine

Reference32 articles.

1. J. Benes, Cutting Difficult Machine Materials, 01/24/2007. http://www.Americanmachinist.com/304/Issue/Article/False./44740/Issue S

2. Advanced Machining Processes;Jain,2009

3. Influence of cryogenic process parameters on microstructure and hardness evolution of AISI D2 tool steel;Nanesa;Int. J. Adv. Manuf. Technol.,2016

4. Influence of cryogenic treatment on the tribological behaviour of AISI H21 tool steel;Korade;Mater. Res.,2019

5. Effects of cryogenic treatment on wear behavior of D6 tool steel;Akhbarizadeh;Mater. Des.,2009

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