A novel minimum-time feedrate schedule method for five-axis sculpture surface machining with kinematic and geometric constraints

A novel minimum-time feedrate schedule method for five-axis sculpture surface machining with... Currently, to satisfy the stringent requirements on the physical properties of sculptured surfaces, workpiece machining attempts to guarantee the level of machining accuracy while improving the efficiency as much as possible. Because of the characteristics of the sculptured surfaces, the machine tool is usually run at a lower feedrate to avoid large impact forces. However, this sacrifices machining time and still may not meet the requirements. This article presents a novel minimum-time feedrate schedule method to improve the machining efficiency for five-axis machining considering the surface characteristic constraints. First, the mapping relationship between the surface characteristic and the kinematical parameters is constructed by analyzing the following error on each axis. After that, the new constraint conditions on machine tool kinematics limitation and its continuity constraints are given to address changes in the curvature. Next, a new acceleration/deceleration feedrate schedule method is presented based on quintic feedrate smooth profile to minimize the impact force as much as possible. Thus, a novel minimum-time feedrate schedule based on the bidirectional feedrate schedule algorithm is proposed to improve machining efficiency while respecting various constraints. Finally, a sculptured surface with varied curvature is used to illustrate the significant reduction in processing time and improvement in surface quality in large curvature region after scheduling. The simulation and experimental results show that the proposed method can improve the machining efficiency while guaranteeing the machining accuracy. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture SAGE

A novel minimum-time feedrate schedule method for five-axis sculpture surface machining with kinematic and geometric constraints

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Publisher
SAGE
Copyright
© IMechE 2018
ISSN
0954-4054
eISSN
2041-2975
D.O.I.
10.1177/0954405418780167
Publisher site
See Article on Publisher Site

Abstract

Currently, to satisfy the stringent requirements on the physical properties of sculptured surfaces, workpiece machining attempts to guarantee the level of machining accuracy while improving the efficiency as much as possible. Because of the characteristics of the sculptured surfaces, the machine tool is usually run at a lower feedrate to avoid large impact forces. However, this sacrifices machining time and still may not meet the requirements. This article presents a novel minimum-time feedrate schedule method to improve the machining efficiency for five-axis machining considering the surface characteristic constraints. First, the mapping relationship between the surface characteristic and the kinematical parameters is constructed by analyzing the following error on each axis. After that, the new constraint conditions on machine tool kinematics limitation and its continuity constraints are given to address changes in the curvature. Next, a new acceleration/deceleration feedrate schedule method is presented based on quintic feedrate smooth profile to minimize the impact force as much as possible. Thus, a novel minimum-time feedrate schedule based on the bidirectional feedrate schedule algorithm is proposed to improve machining efficiency while respecting various constraints. Finally, a sculptured surface with varied curvature is used to illustrate the significant reduction in processing time and improvement in surface quality in large curvature region after scheduling. The simulation and experimental results show that the proposed method can improve the machining efficiency while guaranteeing the machining accuracy.

Journal

Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering ManufactureSAGE

Published: Jun 1, 2018

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