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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