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Adiabatic shear behavior and cutting force prediction modeling of FV520B steel
by
Wang, Yang
, Wei, Zhaocheng
, Yang, Longyun
, Wang, Minjie
, Duan, Chunzheng
in
Adiabatic flow
/ Advanced manufacturing technologies
/ Alloys
/ Chips
/ Constitutive models
/ Cutting force
/ Cutting parameters
/ Cutting speed
/ Cutting wear
/ Deformation
/ Errors
/ Friction
/ Manufacturing
/ Martensitic stainless steels
/ Mathematical models
/ Prediction models
/ Rake angle
/ Shear
/ Shear strain
/ Spindles
/ Strain hardening
/ Teeth
/ Thickness
/ Tool wear
/ Yield stress
2023
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Adiabatic shear behavior and cutting force prediction modeling of FV520B steel
by
Wang, Yang
, Wei, Zhaocheng
, Yang, Longyun
, Wang, Minjie
, Duan, Chunzheng
in
Adiabatic flow
/ Advanced manufacturing technologies
/ Alloys
/ Chips
/ Constitutive models
/ Cutting force
/ Cutting parameters
/ Cutting speed
/ Cutting wear
/ Deformation
/ Errors
/ Friction
/ Manufacturing
/ Martensitic stainless steels
/ Mathematical models
/ Prediction models
/ Rake angle
/ Shear
/ Shear strain
/ Spindles
/ Strain hardening
/ Teeth
/ Thickness
/ Tool wear
/ Yield stress
2023
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Do you wish to request the book?
Adiabatic shear behavior and cutting force prediction modeling of FV520B steel
by
Wang, Yang
, Wei, Zhaocheng
, Yang, Longyun
, Wang, Minjie
, Duan, Chunzheng
in
Adiabatic flow
/ Advanced manufacturing technologies
/ Alloys
/ Chips
/ Constitutive models
/ Cutting force
/ Cutting parameters
/ Cutting speed
/ Cutting wear
/ Deformation
/ Errors
/ Friction
/ Manufacturing
/ Martensitic stainless steels
/ Mathematical models
/ Prediction models
/ Rake angle
/ Shear
/ Shear strain
/ Spindles
/ Strain hardening
/ Teeth
/ Thickness
/ Tool wear
/ Yield stress
2023
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Adiabatic shear behavior and cutting force prediction modeling of FV520B steel
Journal Article
Adiabatic shear behavior and cutting force prediction modeling of FV520B steel
2023
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Overview
FV520B steel is a challenging metal to machine, often exhibiting adiabatic shear behavior during cutting, which leads to the formation of serrated chips. Serrated chips not only cause fluctuations in cutting forces, resulting in a loss of cutting accuracy, but also contribute to rapid tool wear. Therefore, it is crucial to understand the evolution of serrated chips during the cutting process and establish an accurate cutting force model. In this study, we established the serrated chip deformation coefficient and serration factor to analyze the changes in chip morphology based on cutting speed, uncut chip thickness, and tool rake angle. Additionally, a cutting force prediction model was developed using the Johnson–Cook constitutive model, taking into account adiabatic shear damage, and the cutting temperature model proposed by Huang and Liang. The research results found that the serration degree of FV520B steel chips gradually becomes severe with increasing cutting speed, increasing uncut chip thickness, and decreasing tool rake angle. The average errors in predicting cutting forces in the X, Y, and Z directions were 10.3%, 10.5%, and 10.9%, respectively, with maximum errors of 15.5%, 13.4%, and 14.0%. The effect of cutting parameters on FX and FY can be summarized as follows: axial cutting depth > feed per tooth > spindle speed. The effect on FZ can be described as: spindle speed > axial cutting depth > feed per tooth.
Publisher
Springer Nature B.V
Subject
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