Multi-objective optimization of milling process for thin-walled parts

Jiahao Yang; Jingxiang Lv; Yingfeng Zhang

doi:10.1109/ICNSC.2018.8361310

Multi-objective optimization of milling process for thin-walled parts

Jiahao Yang
, Jingxiang Lv
, Yingfeng Zhang

School of Mechanical Engineering

Northwestern Polytechnical University Xian

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

Abstract

In this paper, we recorded the main input parameters of a computer numerical control (CNC) machine during the milling process of the thin-walled parts, including: spindle speed, feed speed, axial depth of cut, radial cutting repetition rate and tool diameter, while collected the output data: the energy consumption, time, dimension accuracy and surface roughness by the devices including current sensors, voltage sensors, etc. After that, further analysis regarding the optimization objective of simultaneously minimum surface roughness, energy consumption and machining time was carried out using Pareto analysis and Weighted Signal-to-Noise Ratio.

Original language	English
Title of host publication	ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1-4
Number of pages	4
ISBN (Electronic)	9781538650530
DOIs	https://doi.org/10.1109/ICNSC.2018.8361310
State	Published - 18 May 2018
Event	15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018 - Zhuhai, China Duration: 27 Mar 2018 → 29 Mar 2018

Publication series

Name	ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control

Conference

Conference	15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018
Country/Territory	China
City	Zhuhai
Period	27/03/18 → 29/03/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

CNC machine
energy
milling
optimize
Pareto analysis
roughness

Access to Document

10.1109/ICNSC.2018.8361310

Cite this

Yang, J., Lv, J., & Zhang, Y. (2018). Multi-objective optimization of milling process for thin-walled parts. In ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control (pp. 1-4). (ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICNSC.2018.8361310

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title = "Multi-objective optimization of milling process for thin-walled parts",

abstract = "In this paper, we recorded the main input parameters of a computer numerical control (CNC) machine during the milling process of the thin-walled parts, including: spindle speed, feed speed, axial depth of cut, radial cutting repetition rate and tool diameter, while collected the output data: the energy consumption, time, dimension accuracy and surface roughness by the devices including current sensors, voltage sensors, etc. After that, further analysis regarding the optimization objective of simultaneously minimum surface roughness, energy consumption and machining time was carried out using Pareto analysis and Weighted Signal-to-Noise Ratio.",

keywords = "CNC machine, energy, milling, optimize, Pareto analysis, roughness",

author = "Jiahao Yang and Jingxiang Lv and Yingfeng Zhang",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018 ; Conference date: 27-03-2018 Through 29-03-2018",

year = "2018",

month = may,

day = "18",

doi = "10.1109/ICNSC.2018.8361310",

language = "英语",

series = "ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "1--4",

booktitle = "ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control",

}

Yang, J, Lv, J & Zhang, Y 2018, Multi-objective optimization of milling process for thin-walled parts. in ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control. ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control, Institute of Electrical and Electronics Engineers Inc., pp. 1-4, 15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018, Zhuhai, China, 27/03/18. https://doi.org/10.1109/ICNSC.2018.8361310

Multi-objective optimization of milling process for thin-walled parts. / Yang, Jiahao; Lv, Jingxiang; Zhang, Yingfeng.
ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-4 (ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control).

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

TY - GEN

T1 - Multi-objective optimization of milling process for thin-walled parts

AU - Yang, Jiahao

AU - Lv, Jingxiang

AU - Zhang, Yingfeng

PY - 2018/5/18

Y1 - 2018/5/18

N2 - In this paper, we recorded the main input parameters of a computer numerical control (CNC) machine during the milling process of the thin-walled parts, including: spindle speed, feed speed, axial depth of cut, radial cutting repetition rate and tool diameter, while collected the output data: the energy consumption, time, dimension accuracy and surface roughness by the devices including current sensors, voltage sensors, etc. After that, further analysis regarding the optimization objective of simultaneously minimum surface roughness, energy consumption and machining time was carried out using Pareto analysis and Weighted Signal-to-Noise Ratio.

AB - In this paper, we recorded the main input parameters of a computer numerical control (CNC) machine during the milling process of the thin-walled parts, including: spindle speed, feed speed, axial depth of cut, radial cutting repetition rate and tool diameter, while collected the output data: the energy consumption, time, dimension accuracy and surface roughness by the devices including current sensors, voltage sensors, etc. After that, further analysis regarding the optimization objective of simultaneously minimum surface roughness, energy consumption and machining time was carried out using Pareto analysis and Weighted Signal-to-Noise Ratio.

KW - CNC machine

KW - energy

KW - milling

KW - optimize

KW - Pareto analysis

KW - roughness

UR - https://www.scopus.com/pages/publications/85048216208

U2 - 10.1109/ICNSC.2018.8361310

DO - 10.1109/ICNSC.2018.8361310

M3 - 会议稿件

AN - SCOPUS:85048216208

T3 - ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control

SP - 1

EP - 4

BT - ICNSC 2018 - 15th IEEE International Conference on Networking, Sensing and Control

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 15th IEEE International Conference on Networking, Sensing and Control, ICNSC 2018

Y2 - 27 March 2018 through 29 March 2018

ER -

Multi-objective optimization of milling process for thin-walled parts

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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