Research Papers

Optimal Workpiece Setup for Time-Efficient and Energy-Saving Five-Axis Machining of Freeform Surfaces

[+] Author and Article Information
Ke Xu

Department of Mechanical and Aerospace
Hong Kong University of
Science and Technology,
Clear Water Bay, Hong Kong

Kai Tang

Hong Kong University of
Science and Technology,
Clear Water Bay, Hong Kong
e-mail: mektang@ust.hk

Manuscript received May 22, 2016; final manuscript received September 15, 2016; published online November 10, 2016. Assoc. Editor: Radu Pavel.

J. Manuf. Sci. Eng 139(5), 051003 (Nov 10, 2016) (16 pages) Paper No: MANU-16-1292; doi: 10.1115/1.4034846 History: Received May 22, 2016; Revised September 15, 2016

Energy consumption in five-axis machining of freeform surfaces can be considerably large for large-size parts. This paper presents a study on how to setup the workpiece in order to minimize the energy consumption without modifying the toolpath itself. For an arbitrary freeform workpiece, the way how it is setup on the working table highly affects the machine's kinematic behavior, which dominates the overall processing time and energy consumption. Taking into account the speed and acceleration limit of each axis of the machine, we first establish the energy consumption model as a function of the workpiece setup. However, this original model involves certain critical physically pertinent coefficients (such as the moment of inertial of a rotary table) which are usually unavailable in practice. Instead, by exploring insightful geometric characteristics of the five-axis machine, an alternative energy consumption model is established which is independent of those hard-to-obtain coefficients. A simple algorithm is then designed to optimize this model. Both computer simulations and physical cutting experiments demonstrate that, when compared with an arbitrary setup, the optimized workpiece setup is able to achieve a significant saving (as much as 50%) in both energy consumption and total machining time, both using a same tool path.

Copyright © 2017 by ASME
Your Session has timed out. Please sign back in to continue.


Liu, X. , Li, Y. , Ma, S. , and Lee, C.-H. , 2015, “ A Tool Path Generation Method for Freeform Surface Machining by Introducing the Tensor Property of Machining Strip Width,” Comput. Aided Des., 66, pp. 1–13. [CrossRef]
Bohez, E. L. , 2002, “ Five-Axis Milling Machine Tool Kinematic Chain Design and Analysis,” Int. J. Mach. Tools Manuf., 42(4), pp. 505–520. [CrossRef]
Lee, R.-S. , and She, C.-H. , 1997, “ Developing a Postprocessor for Three Types of Five-Axis Machine Tools,” Int. J. Adv. Manuf. Technol., 13(9), pp. 658–665. [CrossRef]
Tutunea-Fatan, O. R. , and Feng, H.-Y. , 2004, “ Configuration Analysis of Five-Axis Machine Tools Using a Generic Kinematic Model,” Int. J. Mach. Tools Manuf., 44(11), pp. 1235–1243. [CrossRef]
She, C.-H. , and Chang, C.-C. , 2007, “ Design of a Generic Five-Axis Postprocessor Based on Generalized Kinematics Model of Machine Tool,” Int. J. Mach. Tools Manuf., 47(3–4), pp. 537–545. [CrossRef]
Affouard, A. , Duc, E. , Lartigue, C. , Langeron, J.-M. , and Bourdet, P. , 2004, “ Avoiding 5-Axis Singularities Using Tool Path Deformation,” Int. J. Mach. Tools Manuf., 44(4), pp. 415–425. [CrossRef]
Sørby, K. , 2007, “ Inverse Kinematics of Five-Axis Machines Near Singular Configurations,” Int. J. Mach. Tools Manuf., 47(2), pp. 299–306. [CrossRef]
Lin, Y. , and Shen, Y. , 2003, “ Modelling of Five-Axis Machine Tool Metrology Models Using the Matrix Summation Approach,” Int. J. Adv. Manuf. Technol., 21(4), pp. 243–248. [CrossRef]
Ibaraki, S. , Sawada, M. , Matsubara, A. , and Matsushita, T. , 2010, “ Machining Tests to Identify Kinematic Errors on Five-Axis Machine Tools,” Precis. Eng., 34(3), pp. 387–398. [CrossRef]
Uddin, M. S. , Ibaraki, S. , Matsubara, A. , and Matsushita, T. , 2009, “ Prediction and Compensation of Machining Geometric Errors of Five-Axis Machining Centers With Kinematic Errors,” Precis. Eng., 33(2), pp. 194–201. [CrossRef]
My, C. A. , and Bohez, E. L. , 2016, “ New Algorithm to Minimise Kinematic Tool Path Errors Around 5-Axis Machining Singular Points,” Int. J. Prod. Res., 54(20), pp. 1–11. [CrossRef]
Kordonowy, D. N. , 2002, “ A Power Assessment of Machining Tools,” Massachusetts Institute of Technology, Boston, MA.
Kara, S. , and Li, W. , 2011, “ Unit Process Energy Consumption Models for Material Removal Processes,” CIRP Ann. Manuf. Technol., 60(1), pp. 37–40. [CrossRef]
Diaz, N. , Redelsheimer, E. , and Dornfeld, D. , 2011, “ Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool Use,” Glocalized Solutions for Sustainability in Manufacturing, Springer, Berkeley, CA, pp. 263–267.
Draganescu, F. , Gheorghe, M. , and Doicin, C. , 2003, “ Models of Machine Tool Efficiency and Specific Consumed Energy,” J. Mater. Process. Technol., 141(1), pp. 9–15. [CrossRef]
Aramcharoen, A. , and Mativenga, P. T. , 2014, “ Critical Factors in Energy Demand Modelling for CNC Milling and Impact of Toolpath Strategy,” J. Cleaner Prod., 78, pp. 63–74. [CrossRef]
Diaz, N. , Helu, M. , Jarvis, A. , Tönissen, S. , Dornfeld, D. , and Schlosser, R. , 2009, “ Strategies for Minimum Energy Operation for Precision Machining,” MTTRF 2009 Annual Meeting, Shanghai, China, July 8–9. http://escholarship.org/uc/item/794866g5#
Quintana, G. , Ciurana, J. , and Ribatallada, J. , 2011, “ Modelling Power Consumption in Ball-End Milling Operations,” Mater. Manuf. Process., 26(5), pp. 746–756. [CrossRef]
Dietmair, A. , and Verl, A. , 2009, “ Energy Consumption Forecasting and Optimisation for Tool Machines,” MM Sci. J., 2(1), pp. 63–67. [CrossRef]
Mouzon, G. , Yildirim, M. B. , and Twomey, J. , 2007, “ Operational Methods for Minimization of Energy Consumption of Manufacturing Equipment,” Int. J. Prod. Res., 45(18–19), pp. 4247–4271. [CrossRef]
Newman, S. T. , Nassehi, A. , Imani-Asrai, R. , and Dhokia, V. , 2012, “ Energy Efficient Process Planning for CNC Machining,” CIRP J. Manuf. Sci. Technol., 5(2), pp. 127–136. [CrossRef]
Campatelli, G. , Scippa, A. , Lorenzini, L. , and Sato, R. , 2015, “ Optimal Workpiece Orientation to Reduce the Energy Consumption of a Milling Process,” Int. J. Precis. Eng. Manuf. Green Technol., 2(1), pp. 5–13. [CrossRef]
Anotaipaiboon, W. , Makhanov, S. S. , and Bohez, E. L. , 2006, “ Optimal Setup for Five-Axis Machining,” Int. J. Mach. Tools Manuf., 46(9), pp. 964–977. [CrossRef]
Pessoles, X. , Landon, Y. , Segonds, S. , and Rubio, W. , 2013, “ Optimisation of Workpiece Setup for Continuous Five-Axis Milling: Application to a Five-Axis BC Type Machining Centre,” Int. J. Adv. Manuf. Technol., 65(1), pp. 67–79. [CrossRef]
Shaw, D. , and Ou, G.-Y. , 2008, “ Reducing X, Y and Z Axes Movement of a 5-Axis AC Type Milling Machine by Changing the Location of the Work-Piece,” Comput. Aided Des., 40(10–11), pp. 1033–1039. [CrossRef]
Hu, P. , and Tang, K. , 2011, “ Improving the Dynamics of Five-Axis Machining Through Optimization of Workpiece Setup and Tool Orientations,” Comput. Aided Des., 43(12), pp. 1693–1706. [CrossRef]
Tang, K. , Chen, L.-L. , and Chou, S.-Y. , 1998, “ Optimal Workpiece Setups for 4-Axis Numerical Control Machining Based on Machinability,” Comput. Ind., 37(1), pp. 27–41. [CrossRef]
Kang, J.-K. , and Suh, S.-H. , 1997, “ Machinability and Set-Up Orientation for Five-Axis Numerically Controlled Machining of Free Surfaces,” Int. J. Adv. Manuf. Technol., 13(5), pp. 311–325. [CrossRef]
Hu, P. , Tang, K. , and Lee, C.-H. , 2013, “ Global Obstacle Avoidance and Minimum Workpiece Setups in Five-Axis Machining,” Comput. Aided Des., 45(10), pp. 1222–1237. [CrossRef]
Cai, N. , Wang, L. , and Feng, H.-Y. , 2008, “ Adaptive Setup Planning of Prismatic Parts for Machine Tools With Varying Configurations,” Int. J. Prod. Res., 46(3), pp. 571–594. [CrossRef]
Engin, S. , and Altintas, Y. , 2001, “ Mechanics and Dynamics of General Milling Cutters: Part I: Helical End Mills,” Int. J. Mach. Tools Manuf., 41(15), pp. 2195–2212. [CrossRef]
De Berg, M. , Van Kreveld, M. , Overmars, M. , and Schwarzkopf, O. C. , 2000, Computational Geometry, Springer, Dordrecht, The Netherlands, pp. 1–17.


Grahic Jump Location
Fig. 1

Kinematic chain of a typical five-axis machine with an A–C table

Grahic Jump Location
Fig. 2

The decoupled translational and rotational movement of a tool path after IKT

Grahic Jump Location
Fig. 4

A schematic trend curve of energy consumption versus the latitude

Grahic Jump Location
Fig. 5

To minimize Criterion 1 subject to the TADR constraint

Grahic Jump Location
Fig. 3

Different latitudes yield different rotational movements and energy consumptions

Grahic Jump Location
Fig. 6

Rotating TADR to minimize Criterion 1

Grahic Jump Location
Fig. 8

Visualized Con 1 and Con 2 for a translational movement

Grahic Jump Location
Fig. 7

Computing the horizon of a convex hull

Grahic Jump Location
Fig. 10

Calculate the translational vector CT to satisfy Con 1

Grahic Jump Location
Fig. 9

Energy performance along different directions

Grahic Jump Location
Fig. 11

(a) The test part and (b) its tool path generated by NX

Grahic Jump Location
Fig. 12

A virtue five-axis machine with an A–C tilting table and the reference setup

Grahic Jump Location
Fig. 15

Rotational (a) and translational (b) movements under the optimized setup

Grahic Jump Location
Fig. 13

Rotational (a) and translational (b) movement under the reference setup

Grahic Jump Location
Fig. 14

The optimized setup

Grahic Jump Location
Fig. 19

The freeform surface part and its tool path

Grahic Jump Location
Fig. 20

The reference setup (a) and the optimized setup (b)

Grahic Jump Location
Fig. 26

Recorded active power with (a) the reference setup; (b) the optimized setup

Grahic Jump Location
Fig. 27

Recorded energy consumption

Grahic Jump Location
Fig. 28

A prototype design of the fixture for the optimized setup in the computer simulation

Grahic Jump Location
Fig. 21

The base part representing the fixture for the optimized setup

Grahic Jump Location
Fig. 22

The finished part with (a) the reference setup and (b) the optimized setup

Grahic Jump Location
Fig. 23

Rotational movements under (a) the reference setup and (b) the optimized setup

Grahic Jump Location
Fig. 24

Recorded translational movements of the machine under (a) the reference setup and (b) the optimized setup

Grahic Jump Location
Fig. 25

Simulated motions of the rotary table under the reference setup (a) and (b), and the optimized setup (c) and (d)

Grahic Jump Location
Fig. 16

Regulated motions of the five axes under the reference setup: (a) X-axis, (b) Y-axis, (c) Z-axis, (d) A-axis, and (e)C-axis

Grahic Jump Location
Fig. 17

Regulated motions of the five axes under the optimized setup: (a) X-axis, (b) Y-axis, (c) Z-axis, (d) A-axis, and (e)C-axis

Grahic Jump Location
Fig. 18

JDGR200 five-axis machine (a) and the power measuring setup (b)




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In