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Experimental tests and empirical models of the cutting force and surface roughness when cutting 1Cr13 martensitic stainless steel with a coated carbide tool
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Cutting force prediction is the key issue for planning and optimising the machining process. To explore the cutting of difficult-to-machine 1Cr13 martensitic stainless steel, an orthogonal test was conducted to study the cutting force and surface roughness under the dry, full-width milling. In addition, an empirical model, applied to the exponential forms of the cutting force and surface roughness of 1Cr13 martensitic stainless steel, was established by data processing and linear regression. It can be seen that the significance levels of the influence of cutting parameters on cutting force, surface roughness were cutting depth [Formula: see text], feed per tooth f and cutting speed v during APMT 1135 PDTR coated carbide tool milling of 1Cr13 stainless steel at high speed by testing the significance of regression relationships and their coefficients. It was found that the predictive model offered high accuracy. The cutting parameters that affect the cutting force and surface roughness in milling machining were analysed and the common rules were concluded in this article based on a series of cutting experiments. And those rules can be used as the scientific theory evidence for cutting-parameter selection in the milling machining.
SAGE Publications
Title: Experimental tests and empirical models of the cutting force and surface roughness when cutting 1Cr13 martensitic stainless steel with a coated carbide tool
Description:
Cutting force prediction is the key issue for planning and optimising the machining process.
To explore the cutting of difficult-to-machine 1Cr13 martensitic stainless steel, an orthogonal test was conducted to study the cutting force and surface roughness under the dry, full-width milling.
In addition, an empirical model, applied to the exponential forms of the cutting force and surface roughness of 1Cr13 martensitic stainless steel, was established by data processing and linear regression.
It can be seen that the significance levels of the influence of cutting parameters on cutting force, surface roughness were cutting depth [Formula: see text], feed per tooth f and cutting speed v during APMT 1135 PDTR coated carbide tool milling of 1Cr13 stainless steel at high speed by testing the significance of regression relationships and their coefficients.
It was found that the predictive model offered high accuracy.
The cutting parameters that affect the cutting force and surface roughness in milling machining were analysed and the common rules were concluded in this article based on a series of cutting experiments.
And those rules can be used as the scientific theory evidence for cutting-parameter selection in the milling machining.
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