Details
| Original language | English |
|---|---|
| Pages (from-to) | 221-227 |
| Number of pages | 7 |
| Journal | Procedia CIRP |
| Volume | 31 |
| Publication status | Published - 3 Jun 2015 |
| Event | 15th CIRP Conference on Modelling of Machining Operations, CMMO 2015 - Karlsruhe, Germany Duration: 11 Jun 2015 → 12 Jun 2015 |
Abstract
The surface topography of milled workpieces often defines their performance. One example is blades in turbine engines, where the topography defines the flow losses. This type of complex goods is often machined by ball end mills, either for manufacture or repair. The literature offers various model types to predict the surface topography in order to design a machining process without prior experiment. The most accurate models use the real kinematics of the process and blend the tool with the workpiece. But this type of surface prediction ignores the differences between the reality and the simulation due to vibrations, tool chipping etc. This paper presents a combined approach using the kinematic topography from the machining simulation and adds a stochastic topography based on empirical data. It could be shown, that the usage of the stochastic topography greatly affects the flow losses and thus cannot be ignored.
Keywords
- Milling, Simulation, Topography
ASJC Scopus subject areas
- Engineering(all)
- Control and Systems Engineering
- Engineering(all)
- Industrial and Manufacturing Engineering
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In: Procedia CIRP, Vol. 31, 03.06.2015, p. 221-227.
Research output: Contribution to journal › Conference article › Research › peer review
}
TY - JOUR
T1 - Prediction of the 3D surface topography after ball end milling and its influence on aerodynamics
AU - Denkena, B.
AU - Böß, V.
AU - Nespor, D.
AU - Gilge, P.
AU - Hohenstein, S.
AU - Seume, J.
N1 - Funding information: The authors thank the German Research Foundation (DFG) for the financial support within the Collaborative Research Center 871: Regeneration of complex capital goods. The authors also appreciate the contribution of Karen Mulleners to this paper.
PY - 2015/6/3
Y1 - 2015/6/3
N2 - The surface topography of milled workpieces often defines their performance. One example is blades in turbine engines, where the topography defines the flow losses. This type of complex goods is often machined by ball end mills, either for manufacture or repair. The literature offers various model types to predict the surface topography in order to design a machining process without prior experiment. The most accurate models use the real kinematics of the process and blend the tool with the workpiece. But this type of surface prediction ignores the differences between the reality and the simulation due to vibrations, tool chipping etc. This paper presents a combined approach using the kinematic topography from the machining simulation and adds a stochastic topography based on empirical data. It could be shown, that the usage of the stochastic topography greatly affects the flow losses and thus cannot be ignored.
AB - The surface topography of milled workpieces often defines their performance. One example is blades in turbine engines, where the topography defines the flow losses. This type of complex goods is often machined by ball end mills, either for manufacture or repair. The literature offers various model types to predict the surface topography in order to design a machining process without prior experiment. The most accurate models use the real kinematics of the process and blend the tool with the workpiece. But this type of surface prediction ignores the differences between the reality and the simulation due to vibrations, tool chipping etc. This paper presents a combined approach using the kinematic topography from the machining simulation and adds a stochastic topography based on empirical data. It could be shown, that the usage of the stochastic topography greatly affects the flow losses and thus cannot be ignored.
KW - Milling
KW - Simulation
KW - Topography
UR - http://www.scopus.com/inward/record.url?scp=84939158124&partnerID=8YFLogxK
U2 - 10.1016/j.procir.2015.03.049
DO - 10.1016/j.procir.2015.03.049
M3 - Conference article
AN - SCOPUS:84939158124
VL - 31
SP - 221
EP - 227
JO - Procedia CIRP
JF - Procedia CIRP
SN - 2212-8271
T2 - 15th CIRP Conference on Modelling of Machining Operations, CMMO 2015
Y2 - 11 June 2015 through 12 June 2015
ER -