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Research Papers

Energy Efficiency in Thermally Assisted Machining of Titanium Alloy: A Numerical Study

[+] Author and Article Information
X. Ge

Department of Aerospace
and Mechanical Engineering,
Saint Louis University,
Saint Louis, MO 63103

S. Lei

Department of Industrial
and Manufacturing Systems Engineering,
Kansas State University,
Manhattan, KS 66506

Manuscript received March 21, 2013; final manuscript received September 29, 2013; published online November 5, 2013. Assoc. Editor: Yung Shin.

J. Manuf. Sci. Eng 135(6), 061001 (Nov 05, 2013) (6 pages) Paper No: MANU-13-1097; doi: 10.1115/1.4025610 History: Received March 21, 2013; Revised September 29, 2013

This study investigates the energy utilization and efficiency in thermally assisted machining (TAM) of a titanium alloy using numerical simulation. AdvantEdge finite element method (FEM) is used to conduct the simulation of orthogonal machining of the workpiece. Thermal boundary conditions are specified to approximate laser preheating of the workpiece material. The effects of operating conditions (preheat temperature, cutting speed, depth of cut, and rake angle) on mechanical cutting energy, preheat energy, and energy efficiency are investigated. The results show that preheating the workpiece reduces the cutting energy but increases the total energy in TAM. There is significant potential to maximize total energy efficiency in TAM by optimal design of heating strategies and machining conditions.

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Figures

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Fig. 1

FEM orthogonal machining model

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Fig. 2

Temperature distributions for T = 20 °C, V = 2 m/s, d = 0.2 mm, and α = 0 deg

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Fig. 3

Temperature distributions for T = 600 °C, V = 1 m/s, d = 0.1 mm, and α = 10 deg

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Fig. 6

Variations of energy efficiency with average preheat temperature (α = 10 deg) (a) cutting efficiency and preheat efficiency (b) total efficiency

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Fig. 5

Variations of specific energy with average preheat temperature (α = 10 deg)

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Fig. 4

Temperature distributions for T = 1000 °C, V = 1 m/s, d = 0.1 mm, and α = 10 deg

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Fig. 11

Variations of energy efficiency with depth of cut at fixed boundary temperatures (V = 2 m/s, α = 10 deg)

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Fig. 10

Variations of specific energy with depth of cut at fixed boundary temperatures (V = 2 m/s, α = 10 deg)

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Fig. 9

Variations of energy efficiency with cutting speed at fixed boundary temperatures (d = 0.2 mm, α = 10 deg)

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Fig. 8

Temperature gradient from the workpiece top surface down at a fixed boundary temperature of 1000 °C (d = 0.2 mm, α = 10 deg)

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Fig. 7

Variations of specific energy with cutting speed at fixed boundary temperatures (d = 0.2 mm, α = 10 deg)

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Fig. 12

Variations of specific energy with rake angle at fixed boundary temperatures (V = 2 m/s, d = 0.2 mm)

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Fig. 13

Variations of energy efficiency with rake angle at fixed boundary temperatures (V = 2 m/s, d = 0.2 mm)

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