An Intelligent System for Improving Electric Discharge Machining Efficiency Using Artificial Neural Network and Adaptive Control of Debris Removal Operations
Author:
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science
Link
http://xplorestaging.ieee.org/ielx7/6287639/9312710/09431212.pdf?arnumber=9431212
Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Multi-functional Inconel 625 micro-machining and process optimization using ANFIS;Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering;2024-05-17
2. Machinability of different cutting tool materials for electric discharge machining: A review and future prospects;AIP Advances;2024-04-01
3. Development of forecast models on electrical discharge machined graphene nanoplatelets reinforced aluminum composite fabricated via stir casting route;Cogent Engineering;2024-03-18
4. Importance of industry 4.0 technologies for development of electrical discharge machining;AIP Conference Proceedings;2024
5. Mathematical Models and System of Intelligent Servo for High-Efficiency Electrical Discharge Assisted Arc Milling on Difficult-to-Cut Materials;IEEE Transactions on Systems, Man, and Cybernetics: Systems;2023-09
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