Supervised Machine Learning in Wire Cut Electric Discharge Machining (WEDM)

S. Arungalai Vendan; Rajeev Kamal; Abhinav Karan; Liang Gao; Xiaodong Niu; Akhil Garg

doi:10.1007/978-981-13-9382-2_4

Supervised Machine Learning in Wire Cut Electric Discharge Machining (WEDM)

S. Arungalai Vendan^*, Rajeev Kamal, Abhinav Karan, Liang Gao, Xiaodong Niu, Akhil Garg

^*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceeding › Chapter › peer-review

5 Citations (Scopus)

Abstract

Wire electrical discharge machining (WEDM) technology has grown tremendously since it was first introduced about 40 years back. In 1974, D. H. Dulebohn applied the optical-line follower system to automatically control the shape of the components to be machined by the WEDM process. By 1975, its popularity rapidly increased, as the process and its capabilities were better understood by the industry.

Original language	English
Title of host publication	Engineering Applications of Computational Methods
Publisher	Springer
Pages	187-245
Number of pages	59
DOIs	https://doi.org/10.1007/978-981-13-9382-2_4
Publication status	Published - 2020
Externally published	Yes

Publication series

Name	Engineering Applications of Computational Methods
Volume	1
ISSN (Print)	2662-3366
ISSN (Electronic)	2662-3374

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10.1007/978-981-13-9382-2_4

Cite this

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abstract = "Wire electrical discharge machining (WEDM) technology has grown tremendously since it was first introduced about 40 years back. In 1974, D. H. Dulebohn applied the optical-line follower system to automatically control the shape of the components to be machined by the WEDM process. By 1975, its popularity rapidly increased, as the process and its capabilities were better understood by the industry.",

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AU - Garg, Akhil

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Supervised Machine Learning in Wire Cut Electric Discharge Machining (WEDM)

Abstract

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