An analytical model for predicting specific cutting energy in whirling milling process

Yan He, Lexiang Wang, Yulin Wang, Yufeng Li, Shilong Wang, Yan Wang, Chao Liu

Research output: Contribution to journalArticleResearchpeer-review

Abstract

The specific cutting energy (SCE) of machining processes is a significant indicator for machining sustainability. However, the characteristics of SCE in whirling milling as a promising green process are unknown because of the special material removal mechanism of this process. This paper presents an analytical model for predicting SCE based on the material removal mechanism of whirling milling. The cutting parameters affecting the SCE characteristics are identified considering the un-deformed chip formation. An analytical model is developed as functions of the identified cutting parameters by calculating material removal volume and cutting forces. To validate the proposed model, the analytical model was applied in ball screw shaft whirling milling. The results indicate that the analytical model can be effectively used to predict the SCE with over 90% accuracy. In addition, the effects of cutting parameters and material removal rate (MRR) on SCE were investigated and analyzed based on the proposed model, which can provide valuable information and guidance for the optimal selection of cutting parameters to minimize SCE and improve MRR.

Original languageEnglish
Article number118181
JournalJournal of Cleaner Production
Volume240
DOIs
Publication statusPublished - 28 Aug 2019

Fingerprint

Milling (machining)
Analytical models
Machining
Ball screws
Sustainable development

Keywords

  • whirling milling process
  • specific cutting energy
  • energy model
  • cutting parameters
  • material removal rate

Cite this

He, Yan ; Wang, Lexiang ; Wang, Yulin ; Li, Yufeng ; Wang, Shilong ; Wang, Yan ; Liu, Chao. / An analytical model for predicting specific cutting energy in whirling milling process. In: Journal of Cleaner Production. 2019 ; Vol. 240.
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title = "An analytical model for predicting specific cutting energy in whirling milling process",
abstract = "The specific cutting energy (SCE) of machining processes is a significant indicator for machining sustainability. However, the characteristics of SCE in whirling milling as a promising green process are unknown because of the special material removal mechanism of this process. This paper presents an analytical model for predicting SCE based on the material removal mechanism of whirling milling. The cutting parameters affecting the SCE characteristics are identified considering the un-deformed chip formation. An analytical model is developed as functions of the identified cutting parameters by calculating material removal volume and cutting forces. To validate the proposed model, the analytical model was applied in ball screw shaft whirling milling. The results indicate that the analytical model can be effectively used to predict the SCE with over 90{\%} accuracy. In addition, the effects of cutting parameters and material removal rate (MRR) on SCE were investigated and analyzed based on the proposed model, which can provide valuable information and guidance for the optimal selection of cutting parameters to minimize SCE and improve MRR.",
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An analytical model for predicting specific cutting energy in whirling milling process. / He, Yan ; Wang, Lexiang; Wang, Yulin; Li, Yufeng; Wang, Shilong; Wang, Yan; Liu, Chao.

In: Journal of Cleaner Production, Vol. 240, 118181, 28.08.2019.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - An analytical model for predicting specific cutting energy in whirling milling process

AU - He, Yan

AU - Wang, Lexiang

AU - Wang, Yulin

AU - Li, Yufeng

AU - Wang, Shilong

AU - Wang, Yan

AU - Liu, Chao

PY - 2019/8/28

Y1 - 2019/8/28

N2 - The specific cutting energy (SCE) of machining processes is a significant indicator for machining sustainability. However, the characteristics of SCE in whirling milling as a promising green process are unknown because of the special material removal mechanism of this process. This paper presents an analytical model for predicting SCE based on the material removal mechanism of whirling milling. The cutting parameters affecting the SCE characteristics are identified considering the un-deformed chip formation. An analytical model is developed as functions of the identified cutting parameters by calculating material removal volume and cutting forces. To validate the proposed model, the analytical model was applied in ball screw shaft whirling milling. The results indicate that the analytical model can be effectively used to predict the SCE with over 90% accuracy. In addition, the effects of cutting parameters and material removal rate (MRR) on SCE were investigated and analyzed based on the proposed model, which can provide valuable information and guidance for the optimal selection of cutting parameters to minimize SCE and improve MRR.

AB - The specific cutting energy (SCE) of machining processes is a significant indicator for machining sustainability. However, the characteristics of SCE in whirling milling as a promising green process are unknown because of the special material removal mechanism of this process. This paper presents an analytical model for predicting SCE based on the material removal mechanism of whirling milling. The cutting parameters affecting the SCE characteristics are identified considering the un-deformed chip formation. An analytical model is developed as functions of the identified cutting parameters by calculating material removal volume and cutting forces. To validate the proposed model, the analytical model was applied in ball screw shaft whirling milling. The results indicate that the analytical model can be effectively used to predict the SCE with over 90% accuracy. In addition, the effects of cutting parameters and material removal rate (MRR) on SCE were investigated and analyzed based on the proposed model, which can provide valuable information and guidance for the optimal selection of cutting parameters to minimize SCE and improve MRR.

KW - whirling milling process

KW - specific cutting energy

KW - energy model

KW - cutting parameters

KW - material removal rate

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