New feed rate optimization formulation in a parametric domain for 5-axis milling robots
Chu, Anh My, Duong, Xuan Bien, Bui, Hoang Tung, Nguyen, Van Cong and Le, Chi Hieu ORCID: https://orcid.org/0000-0002-5168-2297 (2019) New feed rate optimization formulation in a parametric domain for 5-axis milling robots. In: ICCSAMA 2019: Advanced Computational Methods for Knowledge Engineering. Advances in Intelligent Systems and Computing, 1121 . Springer, Cham, Switzerland, pp. 403-411. ISBN 978-3030383640 ISSN 2194-5357 (Print), 2194-5365 (Online) (doi:10.1007/978-3-030-38364-0_36)
Full text not available from this repository. (Request a copy)Abstract
When producing a numerical control (NC) program for a 5-axis CNC machine (the so-called milling robot) to mill a sculptural surface, a constant feed rate value is usually assigned based on programmer’s experiences. For this reason, the feed rate in most of NC programs is often not optimized, it is much lower than maximum reachable value. To increase the productivity of the machining process, the feed rate in NC programs for the milling robots need to be maximized. This paper proposes a new feed rate optimization model, of which the objective function and all the kinematic constraints are transformed and expressed explicitly in a parametric domain which is commonly used in the tool path generation process performed by current CAM systems. Thus, the optimal feed rate values along a parametric tool path can be computed in an effective and simplified manner. Numerical examples demonstrate the effectiveness of the proposed method.
Item Type: | Conference Proceedings |
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Title of Proceedings: | ICCSAMA 2019: Advanced Computational Methods for Knowledge Engineering |
Uncontrolled Keywords: | high speed milling, 5-axis milling robot, kinematic modelling, feed rate interpolation |
Subjects: | T Technology > TA Engineering (General). Civil engineering (General) |
Faculty / School / Research Centre / Research Group: | Faculty of Engineering & Science Faculty of Engineering & Science > Design, Manufacturing and Innovative Products Research Theme Faculty of Engineering & Science > School of Engineering (ENG) |
Last Modified: | 19 Sep 2020 00:20 |
URI: | http://gala.gre.ac.uk/id/eprint/26695 |
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