Prediction of Flank Wear in Turning of Monel K500 by Using Machine Learning Model in Comparison With Experimental Analysis-Reference-Cited by-同舟云学术

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Prediction of Flank Wear in Turning of Monel K500 by Using Machine Learning Model in Comparison With Experimental Analysis

Published:2023-12-21 Issue: Volume:20 Page:1-5
ISSN:
Container-title:2023 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI)
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Author:

Dilli Ganesh V¹,Thangaraj S. John Justin²

Affiliation:

1. Saveetha Institute of Medical and Technical Science- SIMATS,Saveetha School of Engineering,Department of Mechanical Engineering,Chennai,Tamilnadu,India

2. Saveetha Institute of Medical and Technical Science- SIMATS,Saveetha School of Engineering,Department of Computer Science Engineering,Chennai,Tamilnadu,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10452407/10452427/10452513.pdf?arnumber=10452513

Reference17 articles.

1. Effect of magneto rheological minimum quantity lubrication on machinability, wettability and tribological behavior in turning of Monel K500 alloy

2. CNN Based Moving Object Detection from Surveillance Video in Comparison with GMM

3. A novel approach of combined edge detection and segmentation for tool wear measurement in machining

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