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Research Papers

Virtual Simulation and Optimization of Milling Applications—Part II: Optimization and Feedrate Scheduling

[+] Author and Article Information
S. Doruk Merdol

Manufacturing Automation Laboratory, Department of Mechanical Engineering,  The University of British Columbia, 6250 Applied Science Lane, Vancouver, BC, V6T 1Z4, Canadadmerdol@mech.ubc.ca

Yusuf Altintas

Manufacturing Automation Laboratory, Department of Mechanical Engineering,  The University of British Columbia, 6250 Applied Science Lane, Vancouver, BC, V6T 1Z4, Canadaaltintas@mech.ubc.ca

J. Manuf. Sci. Eng 130(5), 051005 (Aug 14, 2008) (10 pages) doi:10.1115/1.2927435 History: Received June 27, 2006; Revised March 18, 2007; Published August 14, 2008

The ultimate goal of future manufacturing is to design, test, and manufacture parts in a virtual environment before they are sent to the shop floor. While Part I of this paper presents the modeling of process simulation in a virtual environment, this second part presents computationally efficient algorithms for optimal selection of depth of cut, width of cut, speed, and feed while considering process constraints and variation of the part geometry along the tool path. The objective function is selected as the material removal rate (MRR), and optimization of milling processes is based on user defined constraints, such as maximum tool deflection, torque/power demand, and chatter stability. The MRR is maximized by optimal selection of cutting speed, feed rate, depth, and width of cut. Two alternative optimization strategies are presented. Preprocess optimization provides allowable depth and width of cut during part programming at the computer aided manufacturing stage using chatter constraint, whereas the postprocess optimization tunes only feed rate and spindle speed of an existing part program to maximize productivity without violating torque, power, and tool deflection limits. Optimized feed rates are filtered by considering machine tool axis limitations, and the algorithms are tested in machining a helicopter gear box cover.

Copyright © 2008 by American Society of Mechanical Engineers
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References

Figures

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Figure 5

Cutter workpiece engagement, integration boundaries

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Figure 6

Various intersection scenarios

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Figure 7

Gear box cover: (a) complete solid model (double sided machining), (b) solid model for machining front features, and (c) real cut part with front features

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Figure 8

Stability lobes for full immersion milling (b=1) of (a) 10mm end mill, and (b) 25mm indexable cutter

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Figure 9

10mm end mill: (a) stability lobes; (b) MRR characteristics for various immersion and spindle speeds

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Figure 10

Mori Seiki SH-403-torque/power Characteristics

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Figure 11

Process planning charts for 10mm end mill: (a) stability limited design space, (b) objective function, (c) start angle for down milling, and (d) feed rate

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Figure 12

Process planning charts for 25mm indexable cutter: (a) torque limited design space, (b) objective function, (c) start angle for down milling, and (d) feedrate

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Figure 13

Sample force variation for a uniform pitch cutter

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CEFs and static tool deflection at surface generation point, zgp

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Figure 15

Sample stability lobes

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Figure 1

Design variables

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Figure 2

Dynamics of milling

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Figure 3

Chatter stability lobes for constant (a) radial width of cut; (b) axial depth of cut; (c) design space bounded by chatter stability

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Figure 4

Important parameters for analytical solution: (a) and (c) Case I (ϕcr,0<ϕex); (b) and (d) Case II (ϕcr,0⩾ϕex)

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Figure 16

Graphical representation of design space

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Figure 17

CL file optimization flow diagram (postprocess optimization)

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Figure 18

Feed rate update of linear (G01) and circular (G02-G03) NC blocks

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