Journal
PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY
Volume 61, Issue -, Pages 103-109Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.precisioneng.2019.10.010
Keywords
NC machine tool; Milling operation; Nonlinear friction characteristics; Process damping; Chatter; Simulation
Categories
Funding
- Osawa Scientific Studies Grants Foundation
- JSPS KAKENHI [JP18H01350, JP17H03158]
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A higher machining ability is always required for NC machine tools to achieve higher productivity. The self-oscillated vibration called chatter is a well-known and significant problem that increases the metal removal rate. The generation process of the chatter vibration can be described as a relationship between cutting force and machine tool dynamics. The characteristics of machine tool feed drives are influenced by the nonlinear friction characteristics of the linear guides. Hence, the nonlinear friction characteristics are expected to affect the machining ability of machines. The influence of the contact between the cutting edge and the workpiece (i.e., process damping) on to the machining ability has also been investigated. This study tries to clarify the influence of the nonlinear friction characteristics of linear guides and ball screws and process damping onto milling operations. A vertical-type machining center is modeled by a multi-body dynamics model with nonlinear friction models. The influence of process damping onto the machine tool dynamics is modeled as stiffness and damping between the tool and the workpiece based on the evaluated frequency response during the milling operation. A time domain-coupled simulation approach between the machine tool behavior and the cutting forces is performed by using the machine tool dynamics model. The simulation results confirm that the nonlinear frictions influence the cutting forces with an effect to suppress the chatter vibration. Furthermore, the influence of process damping can be evaluated by the proposed measurement method and estimated by a time domain simulation.
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