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Research Papers

A Two-Dimensional Transient Thermal Model for Coated Cutting Tools

[+] Author and Article Information
Coskun Islam

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

Yusuf Altintas

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

1Corresponding author.

Manuscript received October 17, 2018; final manuscript received April 13, 2019; published online May 14, 2019. Assoc. Editor: Tugrul Ozel.

J. Manuf. Sci. Eng 141(7), 071003 (May 14, 2019) (14 pages) Paper No: MANU-18-1732; doi: 10.1115/1.4043578 History: Received October 17, 2018; Accepted April 15, 2019

Prediction of temperature in the tool, chip, and workpiece surface is important to study tool wear, residual stresses in the machined part, and to design cutting tool substrates and coating. This paper presents a finite difference method-based prediction of temperature distribution in the tool, chip, and workpiece surface for transient conditions. The model allows inclusion of anisotropic materials such as coating or different material properties. The energy is created in the primary shear zone where the metal is sheared, the secondary deformation zone where the chip moves on the tool rake face with friction, and the tertiary zone where the flank face of the tool rubs against the finished part surface. The model allows both sticking and sliding friction contact of the moving chip on the rake face of the tool. The distribution of temperature is evaluated by meshing chip, workpiece surface zone, and tool into small discrete elements. The heat transfer among the elements is modeled, and the temperature is predicted at the center of each element. The heat transfer to the tool, workpiece, and chip is iteratively evaluated. The predicted temperature values are compared against the experimental measurements collected with coated tools in turning.

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Figures

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Fig. 1

Deformation zones in cutting

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Fig. 2

Sample volumetric discretization in physical (Cartesian) and computational (curvilinear) spaces

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Fig. 3

Element to element varying conduction coefficient demonstration

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Fig. 4

Example chip domain

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Fig. 5

Example tool domain

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Fig. 6

Example workpiece domain

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Fig. 7

The flow chart of the temperature prediction algorithm

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Fig. 8

Rake face temperature simulations compared to infrared measurements in Ref. [33] for turning of SS2541 steel at V = 3.33 m/s and f = 0.1 mm/rev with TiN coated tool after 100 ms cutting time

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Fig. 9

Average rake face temperature and heat partition variation with time for turning of SS2541 steel with TiN coated tool at V = 3.33 m/s cutting speed and 0.1 mm/rev and 0.15 mm/rev feed rates

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Fig. 10

Simulated temperature distributions at steady-state for turning of SS2541 steel at V = 3.33 m/s and f = 0.1 mm/rev with TiN coating after 100 ms cutting time

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Fig. 11

Average rake face temperature and heat partition variation with time for turning of AISI 1045 steel at V = 2.4, 2.07, and 1.48 m/s, and f = 0.16 mm/rev with TiC/Al2O3/TiN coated tool

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Fig. 12

Simulated temperature distributions at the steady-state condition for turning of AISI 1045 steel at V = 2.4 m/s and f = 0.16 mm/rev with TiC/Al2O3/TiN coating after 100 ms cutting time

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Fig. 13

Sticking and sliding contact's effect on the tool–chip interface temperature for Ti6Al4V

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Fig. 14

Convection coefficient sensitivity of the simulations for Ti6Al4V

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Fig. 15

Comparison of temperature gradients for turning of Ti6Al4V at V = 100 m/min and f = 0.1 mm/rev (a) without or (b) with tool flank face contact assumption

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