Roughness prediction of end milling surface for behavior mapping of digital twined machine tools

Suiyan Shang; Gedong Jiang; Zheng Sun; Wenwen Tian; Dawei Zhang; Jun Xu; Chi Fai Cheung

doi:10.12688/digitaltwin.17819.2

Roughness prediction of end milling surface for behavior mapping of digital twined machine tools

Suiyan Shang, Gedong Jiang, Zheng Sun, Wenwen Tian, Dawei Zhang, Jun Xu, Chi Fai Cheung

Research output: Journal article publication › Journal article › Academic research › peer-review

Abstract

The quality of machined parts is considered as a relevant factor to evaluate the production performance of machine tools. For mapping the production performance into a digital twin machine tool, a virtual metrology model for surface roughness prediction, which affects products' mechanical capacity and aesthetic performance, is proposed in this paper.

Original language	English
Pages (from-to)	on-line version
Journal	Digital Twin
Volume	3
Issue number	4
DOIs	https://doi.org/10.12688/digitaltwin.17819.2
Publication status	Published - 29 Jan 2024

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10.12688/digitaltwin.17819.2

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title = "Roughness prediction of end milling surface for behavior mapping of digital twined machine tools",

abstract = "The quality of machined parts is considered as a relevant factor to evaluate the production performance of machine tools. For mapping the production performance into a digital twin machine tool, a virtual metrology model for surface roughness prediction, which affects products' mechanical capacity and aesthetic performance, is proposed in this paper.",

author = "Suiyan Shang and Gedong Jiang and Zheng Sun and Wenwen Tian and Dawei Zhang and Jun Xu and Cheung, \{Chi Fai\}",

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AU - Shang, Suiyan

AU - Jiang, Gedong

AU - Sun, Zheng

AU - Tian, Wenwen

AU - Zhang, Dawei

AU - Xu, Jun

AU - Cheung, Chi Fai

PY - 2024/1/29

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AB - The quality of machined parts is considered as a relevant factor to evaluate the production performance of machine tools. For mapping the production performance into a digital twin machine tool, a virtual metrology model for surface roughness prediction, which affects products' mechanical capacity and aesthetic performance, is proposed in this paper.

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DO - 10.12688/digitaltwin.17819.2

M3 - Journal article

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SP - on-line version

JO - Digital Twin

JF - Digital Twin

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Roughness prediction of end milling surface for behavior mapping of digital twined machine tools

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