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research-article

Modeling and Analysis of Forces in Laser Assisted Micro Milling

[+] Author and Article Information
Mukund Kumar, Shreyes N. Melkote

George W. Woodruff School of Mechanical Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332

Chia-Jung Chang

Harold and Inge Marcus Department of Industrial and Manufacturing Engineering,
The Pennsylvania State University,
University Park, PA 16802

V. Roshan Joseph

H. Milton Stewart School of Industrial and Systems Engineering,
Georgia Institute of Technology,
Atlanta, GA 30332

Contributed by the Manufacturing Engineering Division of ASME for publication in the Journal of Manufacturing Science and Engineering. Manuscript received October 21, 2012; final manuscript received April 16, 2013; published online July 17, 2013. Assoc. Editor: Y. B. Guo.

J. Manuf. Sci. Eng 135(4), 041018 (Jul 17, 2013) (10 pages) Paper No: MANU-12-1316; doi: 10.1115/1.4024538 History: Received October 21, 2012; Revised April 16, 2013; Accepted April 17, 2013

Laser assisted micro milling (LAMM) is capable of generating three dimensional microscale features in hard metals with lower cutting forces than conventional micro milling. To maximize the reduction in cutting forces, a mathematical model is required to understand the influence of different laser and machining parameters on the forces. Consequently, a physics-based force model is developed in this paper to predict the cutting forces when micro milling a hard metal using laser assist. LAMM experiments are carried out on 52,100 bearing steel (62 HRc) over a range of feed rates and laser powers to calibrate the force model. The results indicate that the model predicts the cutting force profile with good accuracy. This model is then used to study the influence of laser assist on cutting forces, which yields a better physical understanding of the LAMM process.

Copyright © 2013 by ASME
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References

Aramcharoen, A., Mativenga, P. T., Yang, S., Cooke, K. E., and Teer, D. G., 2008, “Evaluation and Selection of Hard Coatings for Micro Milling of Hardened Tool Steel,” Int. J. Mach. Tools Manuf., 48, pp. 1578–1584. [CrossRef]
Bissacco, G., Hansen, H. N., and De Chiffre, L., 2005, “Micromilling of Hardened Tool Steel for Mould Making Applications,” J. Mater. Process. Technol., 167, pp. 201–207. [CrossRef]
Bissacco, G., Hansen, H. N., and De Chiffre, L., 2006, “Size Effects on Surface Generation in Micro Milling of Hardened Tool Steel,” CIRP Ann.—Manuf. Technol., 55(1), pp. 593–596. [CrossRef]
Melkote, S., Kumar, M., Hashimoto, F., and Lahoti, G., 2009, “Laser Assisted Micro-Milling of Hard-to-Machine Materials,” CIRP Ann.—Manuf. Technol., 58(1), pp. 45–48. [CrossRef]
Li, P., Oosterling, J. A. J., and Hoogstrate, A. M., 2007, “Performance Evaluation of Micromilling of Hardened Tool Steel,” Proceedings of the International Conference on Micro Manufacturing (ICOMM), Clemson, SC, pp. 219–224.
Anderson, M., Patwa, R., and Shin, Y. C., 2006, “Laser-Assisted Machining of Inconel 718 With an Economic Analysis,” Int. J. Mach. Tools Manuf., 46, pp. 1879–1891. [CrossRef]
Dumitrescu, P., Koshy, P., Stenekes, J., and Elbestawi, M. A., 2006, “High-Power Diode Laser Assisted Hard Turning of AISI D2 Tool Steel,” Int. J. Mach. Tools Manuf., 46, pp. 2009–2016. [CrossRef]
Pfefferkorn, F. E., Incropera, F. P., Shin, Y. C., and Tian, Y., 2004, “Laser-Assisted Machining of Magnesia-Partially-Stabilized Zirconia,” ASME J. Manuf. Sci. Eng., 126, pp. 42–51. [CrossRef]
Rajagopal, S., Plankenhorn, D. J., and Hill, V. L., 1982, “Machining Aerospace Alloys With the Aid of a 15 KW Laser,” J. Appl. Met. Work., 2, pp. 170–184. [CrossRef]
Rozzi, J. C., Incropera, F. P., and Shin, Y. C., 2000, “Transient Three-Dimensional Heat Transfer Model for the Laser Assisted Machining of Silicon Nitride: II. Assessment of Parametric Effects,” Int. J. Heat Mass Transfer, 43, pp. 1425–1437. [CrossRef]
Singh, R., and Melkote, S. N., 2005, “Experimental Characterization of Laser-Assisted Mechanical Micromachining (LAMM) Process,” Proceedings of ASME International Mechanical Engineering Congress and Exposition (IMECE), Vol. 16(2), pp. 957–964.
Singh, R., and Melkote, S. N., 2007, “Characterization of a Hybrid Laser-Assisted Mechanical Micromachining (LAMM) Process for a Difficult-to-Machine Material,” Int. J. Mach. Tools Manuf., 47, pp. 1139–1150. [CrossRef]
Jeon, Y., and Pfefferkorn, F., 2008, “Effect of Laser Preheating the Workpiece on Micro End Milling of Metals,” ASME J. Manuf. Sci. Eng., 130, p. 011004. [CrossRef]
Shelton, J. A., and Shin, Y. C., 2010, “Experimental Evaluation of Laser-Assisted Micromilling in a Slotting Configuration,” ASME J. Manuf. Sci. Eng., 132, p. 021008. [CrossRef]
Singh, R., and Melkote, S. N., 2007, “Force Modeling in Laser-Assisted Micro-Grooving Including the Effect of Machine Deflection,” ASME J. Manuf. Sci. Eng., 131(1), p. 011013. [CrossRef]
Singh, R. K., Joseph, V. R., and Melkote, S. N., 2011, “A Statistical Approach to the Optimization of a Laser-Assisted Micromachining Process,” Int. J. Adv. Manuf. Technol., 53, pp. 221–230. [CrossRef]
Afazov, S. M., Ratchev, S. M., and Segal, J., 2010, “Modelling and Simulation of Micro-Milling Cutting Forces,” J. Mater. Process. Technol., 210, pp. 2154–2162. [CrossRef]
Bao, W. Y., and Tansel, I. N., 2000, “Modeling Micro-End-Milling Operations. Part III: Influence of Tool Wear,” Int. J. Mach. Tools Manuf., 40, pp. 2193–2211. [CrossRef]
Bao, W. Y., and Tansel, I. N., 2000, “Modeling Micro-End-Milling Operations. Part II: Tool Runout,” Int. J. Mach. Tools Manuf., 40, pp. 2175–2192. [CrossRef]
Bao, W. Y., and Tansel, I. N., 2000, “Modeling Micro-End-Milling Operations. Part I: Analytical Cutting Force Model,” Int. J. Mach. Tools Manuf., 40, pp. 2155–2173. [CrossRef]
Bissacco, G., Hansen, H. N., and Slunsky, J., 2008, “Modelling the Cutting Edge Radius Size Effect for Force Prediction in Micro Milling,” CIRP Ann.—Manuf. Technol., 57(1), pp. 113–116. [CrossRef]
Ding, H., Shen, N., and Shin, Y. C., 2012, “Themal and Mechanical Analysis of Laser-Assisted Micro-Milling of Difficult-to-Machine Alloys,” J. Mater. Process. Technol., 212, pp. 601–613. [CrossRef]
Kumar, M., and Melkote, S. N., 2011, “Process Capability Study of Laser Assisted Micro Milling of a Hard-to-Machine Material,” J. Manuf. Process., 14, pp. 41–51. [CrossRef]
Budak, E., Altintas, Y., and Armarego, E. J. A., 1996, “Prediction of Milling Force Coefficients From Orthogonal Cutting Data,” ASME J. Manuf. Sci. Eng., 118, pp. 216–224. [CrossRef]
Carslaw, H. C., and Jaeger, J. C., 1959, Conduction of Heat in Solids, Clarendon, Oxford, UK.
Loewen, E. G., and Shaw, M. C., 1954, “On Analysis of Cutting-Tool Temperatures,” Trans. ASME, 76, pp. 217–225.
Wright, P. K., 1982, “Predicting the Shear Angle in Machining From Workmaterial Strain-Hardening Characteristics,” ASME J. Eng. Ind., 104, pp. 285–292. [CrossRef]
Guo, Y. B., and Liu, C. R., 2002, “Mechanical Properties of Hardened AISI 52100 Steel in Hard Machining Processes,” ASME J. Manuf. Sci. Eng., 124, pp. 1–9. [CrossRef]
Marsh, E. R., 2008, Precision Spindle Metrology, DEStech Publications, Lancaster, PA.
Altintas, Y., 2000, Manufacturing Automation, Cambridge University, Cambridge, UK.
Arsecularatne, J. A., Mathew, P., and Oxley, P. L. B., 1995, “Prediction of Chip Flow Direction and Cutting Forces in Oblique Machining With Nose Radius Tools,” Proc. Inst. Mech. Eng., Part B, 209, pp. 305–315. [CrossRef]
Lin, G. C. I., Mathew, P., Oxley, P. L. B., and Watson, A. R., 1982, “Predicting Cutting Forces for Oblique Machining Conditions,” Proc. Inst. Mech. Eng., 196, pp. 141–148. [CrossRef]
Stabler, G. V., 1951, “The Fundamental Geometry of Cutting Tools,” Proc. Inst. Mech. Eng., 1847–1982 (Vols. 1–196), 165, pp. 14–26. [CrossRef]
Cverna, F., 2002, Thermal Properties of Metals, ASM International, Materials Park, OH.

Figures

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Fig. 1

Overall LAMM force prediction methodology

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Fig. 2

Flowchart of the force prediction methodology

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Fig. 3

Geometry of an end mill (a) front view, and (b) end view showing the elemental forces (suffix “d” refers to dynamometer coordinate system)

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Fig. 4

Cutter tooth path indicating the cutting forces; temperature rise is predicted at equispaced points 1–11, 18 deg apart along the tooth path

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Fig. 5

Calculated temperature rise due to laser heating averaged along the depth of cut (20 μm) at discrete points along the tooth path of a 180 μm diameter tool (see Fig. 4) (AISI 52100 steel, laser power: 18 W, scan speed: 660 mm/min, distance between center of laser beam and edge of cutting tool: 200 μm)

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Fig. 6

Calculated temperature rise due to shear (feed: 6.6 μm/flute, axial depth of cut: 20 μm, spindle speed: 50,000 rpm, no laser assist)

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Fig. 7

Temperature dependence of the yield and ultimate tensile strengths of 52,100 steel (62 HRc) [27]

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Fig. 8

Measurement of runout parameters

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Fig. 9

Power spectrum of a measured force signal (feed: 2.2 μm/flute, depth of cut: 16 μm, and laser power: 18 W)

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Fig. 10

Comparison of the predicted and measured cutting forces

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Fig. 11

Predicted cutting forces with its 95% prediction interval of the validation experiment (depth of cut: 16 μm, and laser power: 18 W): (a) 2.2 μm/flute, (b) 4.4 μm/flute, and (c) 6.6 μm/flute.

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Fig. 12

Comparison of predicted radial (Fr) and tangential (Ft) cutting forces acting on a cutter tooth with and without laser assist over one tool rotation (feed: 6.6 μm/flute, depth of cut: 16 μm, and laser power: 18 W, no runout, β: 48 deg)

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Fig. 13

Variation of shear yield strength (MPa), temperature rise ( °C) and uncut chip thickness (mm) for one of the flutes over one full cycle (feed: 6.6 μm/flute, depth of cut: 16 μm, and laser power: 18 W, no runout, β: 48 deg)

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Fig. 14

Comparison of predicted radial (Fr) and tangential (Ft) cutting forces for one of the flutes with and without laser assist over one full cycle (feed: 6.6 μm/flute, depth of cut: 16 μm, and laser power: 35 W, no runout, β: 48 deg)

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Fig. 15

Comparison of predicted radial (Fr) and tangential (Ft) cutting forces for one of the flutes with and without laser assist over one full cycle (feed: 6.6 μm/flute, depth of cut: 16 μm, and laser power: 18 W, runout parameters: A:1.8 μm, B: −0.5 μm, β: 48 deg)

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