Computational analysis of turning G10530 steel to eliminate chip crowding using variable cutting speeds

Computational analysis of turning G10530 steel to eliminate chip crowding using variable cutting... The machining of axle hub flange housings manufactured using G10530 steel is described in this paper. The machining of axle hub flange housings can lead to the entanglement of chips around workpiece holding fixtures, which leads to a loss of productivity due to the interruption of the machining process to remove entangled machining chips in the vicinity of the chuck (chip crowding). The finite element (FE) method was used to predict machining characteristics in order to eliminate the phenomenon of ‘chip crowding’ around rotating machine parts that impede the effective machining of axle hub flange housings. The finite element method is compared to traditional analytical calculations to observe whether discrete computations can accurately predict machining characteristics and to visually predict the shape of chips to eliminate the possibility of ‘chip crowding’. From this study, it is shown that short chips can be created using variable cutting speeds and that the FE method can be used to analyze chip formations in order to optimize the turning of G10530 axle hub flange housings. For the current practice of machining axle hub housings, when fedge/tr = 0.25 (small cutting edge radius), the level of power required for chip formation is calculated to be 6400 W generating a maximum temperature at the onset of chip formation of ~563 °C, and when fedge/tr = 0.75 (large cutting edge radius), the level of power required for chip formation is calculated to be 3200 W generating a maximum temperature at the onset of chip formation of ~292 °C. When forming chips at variable cutting speeds, the best case condition is one that draws the least power and generates the lowest temperature at the chip tool interface. This is achieved when a large cutting edge radius tool (fedge/tr = 0.75) is used for machining axle hub flanges. Closed form solutions appear to describe the machining conditions at the steady-state conditions very accurately. However, the FE method tends to generate accurate values under the conditions of unsteady chip formation when cutting at variable speeds. The innovations presented in this paper are associated with providing the necessary information to machine axle hub flanges with variable cutting speeds that eliminate the occurrence of ‘chip crowding’ by naturally fragmenting the formation of long metal chips. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png The International Journal of Advanced Manufacturing Technology Springer Journals

Computational analysis of turning G10530 steel to eliminate chip crowding using variable cutting speeds

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Publisher
Springer London
Copyright
Copyright © 2017 by Springer-Verlag London
Subject
Engineering; Industrial and Production Engineering; Media Management; Mechanical Engineering; Computer-Aided Engineering (CAD, CAE) and Design
ISSN
0268-3768
eISSN
1433-3015
D.O.I.
10.1007/s00170-017-0279-0
Publisher site
See Article on Publisher Site

Abstract

The machining of axle hub flange housings manufactured using G10530 steel is described in this paper. The machining of axle hub flange housings can lead to the entanglement of chips around workpiece holding fixtures, which leads to a loss of productivity due to the interruption of the machining process to remove entangled machining chips in the vicinity of the chuck (chip crowding). The finite element (FE) method was used to predict machining characteristics in order to eliminate the phenomenon of ‘chip crowding’ around rotating machine parts that impede the effective machining of axle hub flange housings. The finite element method is compared to traditional analytical calculations to observe whether discrete computations can accurately predict machining characteristics and to visually predict the shape of chips to eliminate the possibility of ‘chip crowding’. From this study, it is shown that short chips can be created using variable cutting speeds and that the FE method can be used to analyze chip formations in order to optimize the turning of G10530 axle hub flange housings. For the current practice of machining axle hub housings, when fedge/tr = 0.25 (small cutting edge radius), the level of power required for chip formation is calculated to be 6400 W generating a maximum temperature at the onset of chip formation of ~563 °C, and when fedge/tr = 0.75 (large cutting edge radius), the level of power required for chip formation is calculated to be 3200 W generating a maximum temperature at the onset of chip formation of ~292 °C. When forming chips at variable cutting speeds, the best case condition is one that draws the least power and generates the lowest temperature at the chip tool interface. This is achieved when a large cutting edge radius tool (fedge/tr = 0.75) is used for machining axle hub flanges. Closed form solutions appear to describe the machining conditions at the steady-state conditions very accurately. However, the FE method tends to generate accurate values under the conditions of unsteady chip formation when cutting at variable speeds. The innovations presented in this paper are associated with providing the necessary information to machine axle hub flanges with variable cutting speeds that eliminate the occurrence of ‘chip crowding’ by naturally fragmenting the formation of long metal chips.

Journal

The International Journal of Advanced Manufacturing TechnologySpringer Journals

Published: Mar 31, 2017

References

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