Tunç, Lütfi Taner (2019) Smart tool path generation for 5-axis ball-end milling of sculptured surfaces using process models. Robotics and Computer Integrated Manufacturing, 56 . pp. 212-221. ISSN 0736-5845 (Print) 1879-2537 (Online)
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Official URL: http://dx.doi.org/10.1016/j.rcim.2018.10.002
Abstract
Efficient 5-axis milling of free form surfaces required smart parameter selection and tool path generation approaches. Current computer-aided manufacturing (CAM) technology offers limited flexibility and assistance for
such purposes, where purely geometrical issues are considered. Consequently, the generated tool path may be off the high-performance milling parameters. In 5-axis milling, the efficient process parameter set usually vary along
the tool path due to varying engagement conditions because of inherent reasons. In this paper, a novel approach is proposed for identification of efficient surface milling parameters according to the variation of cutting forces and stability along the tool path, and then continuously implementation of these parameters for smart tool path generation, obeying the geometrical requirements. The proposed approach is applied on representative cases relevant to industrial applications to demonstrate the benefits. It is shown that, use of process simulations in tool path planning and generation offers significant benefits in decreasing the total cycle time in 5-axis milling.
Item Type: | Article |
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Uncontrolled Keywords: | Simulation, Tool path, 5-axis milling |
Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TS Manufactures > TS0200 Metal manufactures. Metalworking |
Divisions: | Integrated Manufacturing Technologies Research and Application Center Faculty of Engineering and Natural Sciences > Academic programs > Industrial Engineering Faculty of Engineering and Natural Sciences > Academic programs > Manufacturing Systems Eng. Faculty of Engineering and Natural Sciences |
Depositing User: | Lütfi Taner Tunç |
Date Deposited: | 27 May 2019 15:26 |
Last Modified: | 06 Jun 2023 12:37 |
URI: | https://research.sabanciuniv.edu/id/eprint/37084 |