Determination of optimum geometries for a planar re-configurable machining platform using the LFOPC optimization algorithm

Optimum geometries of a re-configurable planar Gough–Stewart machining platform are determined for kinematically prescribed tool paths. The optimization is done via the Leap-Frog OPtimizer for Constrained problems (LFOPC) by the second author. The five geometrical design variables correspond to the...

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Bibliographic Details
Published in:Mechanism and machine theory Vol. 41; no. 3; pp. 307 - 333
Main Authors: du Plessis, L.J., Snyman, J.A.
Format: Journal Article
Language:English
Published: Oxford Elsevier Ltd 01.03.2006
New York, NY Elsevier
Subjects:
Applied sciences
Constrained optimization
Drives
Exact sciences and technology
Inverse dynamics
Linkage mechanisms, cams
Mechanical engineering. Machine design
Optimal design
Re-configurable planar Gough–Stewart machining platform
Trajectory-planning
Re-configurable planar Gough–Stewart machining platform
Trajectory-planning
Inverse dynamics
Optimal design
Constrained optimization
Positioning
Optimal trajectory
Linkage mechanism
Machining
Parallel mechanism
Feasibility
Cutting tool
Experimental study
Force control
Modeling
Optimization
Actuator
ISSN:0094-114X, 1873-3999
Online Access:Get full text
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Summary:Optimum geometries of a re-configurable planar Gough–Stewart machining platform are determined for kinematically prescribed tool paths. The optimization is done via the Leap-Frog OPtimizer for Constrained problems (LFOPC) by the second author. The five geometrical design variables correspond to the placement of the machine relative to the prescribed path and the positioning of the actuator joints on the base and on the moving platform. The objective is to minimize the dynamic actuator forces required for executing the prescribed path, subject to constraints on the geometry and the ranges of actuator lengths. In presenting the fundamental optimization methodology, relative simple numerical experiments are performed, in order to illustrate the feasibility of the proposed optimization approach to the design problem.
ISSN:0094-114X
1873-3999
DOI:10.1016/j.mechmachtheory.2005.05.006