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Research Papers

A Three-Dimensional Transient Thermal Model for Machining

[+] Author and Article Information
Coskun Islam

Manufacturing Automation Laboratory (MAL),
Department of Mechanical Engineering,
University of British Columbia,
2054-6250 Applied Science Lane,
Vancouver, BC V6T 1Z4, Canada
e-mail: coskunislam@alumni.ubc.ca

Ismail Lazoglu

Professor
Manufacturing and Automation Research Center,
Department of Mechanical Engineering,
Koc University,
Rumeli Feneri Yolu,
Sariyer, Istanbul 34450, Turkey
e-mail: ilazoglu@ku.edu.tr

Yusuf Altintas

Professor
Fellow ASME
Manufacturing Automation Laboratory (MAL),
Department of Mechanical Engineering,
University of British Columbia,
2054-6250 Applied Science Lane,
Vancouver, BC V6T 1Z4, Canada
e-mail: altintas@mech.ubc.ca

1Corresponding author.

Contributed by the Manufacturing Engineering Division of ASME for publication in the JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING. Manuscript received November 13, 2014; final manuscript received March 27, 2015; published online September 9, 2015. Assoc. Editor: Radu Pavel.

J. Manuf. Sci. Eng 138(2), 021003 (Sep 09, 2015) (17 pages) Paper No: MANU-14-1590; doi: 10.1115/1.4030305 History: Received November 13, 2014

This article presents an enhanced mathematical model for transient thermal analysis in machining processes. The proposed mathematical model is able to simulate transient tool, workpiece, and chip temperature fields as a function of time for interrupted processes with time varying chip loads such as milling and continuous machining processes such as turning and drilling. A finite difference technique with implicit time discretization is used for the solution of partial differential equations to simulate the temperature fields on the tool, workpiece, and chip. The model validations are performed with the experimental temperature measurement data available in the literature for the interrupted turning of Ti6Al6V–2Sn, Al2024, gray cast iron and for the milling of Ti6Al4V. The simulation results and experimental measurements agree well. With the newly introduced modeling approach, it is demonstrated that time-dependent dynamic variations of the temperature fields are predicted with maximum 12% difference in the validated cases by the proposed transient thermal model.

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References

Figures

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Fig. 1

Discretization of milling cutter as an assembly of differential oblique cutting edges [25]

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Fig. 2

Components of force and velocity on the normal plane for discrete oblique cutting edge

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Fig. 7

Grid point generation in a sample substructure

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Fig. 6

Layout of tool, chip, and workpiece substructures for a turning case

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Fig. 5

Illustration of discretized cutting geometry and elementary substructure geometries

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Fig. 4

One-to-one transformation between Cartesian and curvilinear coordinates

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Fig. 3

Representation of discrete elements of chip in the Cartesian coordinates along with discrete time intervals

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Fig. 8

Recursive algorithm for calculation of transient temperature fields in the chip, workpiece, and tool

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Fig. 12

Ti6Al6V–2Sn evolution of tool and chip thermal fields in heating and cooling cycles with time. See Fig. 11 for corresponding time intervals.

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Fig. 13

Chip temperature distributions Ti6Al6V–2Sn at 50 ms. Cutting conditions: continuous cutting, V = 1.67 m/s, feed rate f = 0.1 mm/rev.

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Fig. 14

Tool temperature distributions Ti6Al6V–2Sn at 50 ms. Cutting conditions: continuous cutting, V = 1.67 m/s, feed rate f = 0.1 mm/rev. Tool geometry: rake angle = 6 deg.

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Fig. 15

Workpiece temperature distributions Ti6Al6V–2Sn at 50 ms. Cutting conditions: continuous cutting, V = 1.67 m/s, feed rate f = 0.1 mm/rev.

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Fig. 16

Simulated and measured average rake face temperature along time in interrupted turning of Al2024 at the feed rate of 0.109 mm/rev [9]

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Fig. 17

Simulated and measured average rake face temperature along time in interrupted turning of Al2024 at the feed rate of 0.165 mm/rev [9]

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Fig. 9

Comparison of the simulation results and experimental measurements [31] on the rake face temperature for Ti6Al6V–2Sn in interrupted turning. Cutting conditions: cutting speed V = 1.67 m/s, feed rate f = 0.1 mm/rev.

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Fig. 10

Computed average heat partition of the tool along time in the continuous machining of Ti6Al6V–2Sn. Cutting conditions: cutting speed V = 1.67 m/s and feed rate f = 0.1 mm/rev.

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Fig. 11

Transient rake face temperature in heating and cooling cycles in interrupted machining of Ti6Al6V–2Sn. Cutting conditions: V = 1.67 m/s and feed rate f = 0.1 mm/rev.

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Fig. 18

Simulated and measured average rake face temperature along time in interrupted turning of gray cast iron [9]

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Fig. 19

Simulated and measured resultant cutting forces and temperature (0.1 mm below rake face) in down milling of Ti6Al4V (a) cutting force and (b) temperature. See Ref. [34] for experimental measurements.

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