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Research Papers

Feedrate Optimization for Computer Numerically Controlled Machine Tools Using Modeled and Measured Process Constraints

[+] Author and Article Information
Sepehr Zarif Mansour

Engineering Department,
UBC,
Kelowna, BC V1V1V7, Canada
e-mail: sepehr.zmansoor@gmail.com

Rudolf Seethaler

Engineering Department,
UBC,
Kelowna, BC V1V1V7, Canada
e-mail: rudolf.seethaler@ubc.ca

Manuscript received March 4, 2016; final manuscript received June 10, 2016; published online August 15, 2016. Assoc. Editor: Radu Pavel.

J. Manuf. Sci. Eng 139(1), 011012 (Aug 15, 2016) (9 pages) Paper No: MANU-16-1142; doi: 10.1115/1.4033933 History: Received March 04, 2016; Revised June 10, 2016

Feedrate optimization for computer numerically controlled (CNC) machine tools is a challenging task that is growing in importance as manufacturing industry demands faster machine tools. The majority of research in this area focusses on optimizing feedrate using modeled process constraints. Some researchers have suggested using measured process parameters instead. The former approach suffers from uncertainties in the modeled process data that is the starting point of the optimization. The latter approach has difficulties achieving high levels of optimality. This study proposes the combination of both modeled and measured process data. To this end, a control architecture is described that allows combining measured and modeled process constraints. Within this architecture, a new algorithm to determine time optimum feedrates using modeled velocity and acceleration constraints is proposed. The new control structure including the novel feedrate optimization algorithm is verified experimentally on a high speed biaxial table.

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Figures

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Fig. 1

CNC architectures based on modeled and measured process data

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Fig. 2

Proposed control architecture

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Fig. 3

Feedrate modulation (a) 100% feedrate override and (b) 50% feedrate override

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Fig. 4

Flowchart of the feedrate optimization algorithm using modeled axis constraints

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Fig. 5

Experimental biaxial table

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Fig. 7

Teardrop reference path

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Fig. 8

Unconstrained velocity and acceleration and their constraint values

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Fig. 9

Model-based feedrate optimization (a) reference velocities using Dong and Stori [11], (b) reference acceleration using Dong and Stori [11], (c) reference velocity using the proposed algorithm, (d) reference acceleration using the proposed algorithm, (e) measured velocity using the proposed algorithm, and (f) measured acceleration using the proposed algorithm

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