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Development of a combined simulation-model for the prediction of process- and machine-induced deviations of surface areas in broaching

Subject Area Metal-Cutting and Abrasive Manufacturing Engineering
Term from 2010 to 2016
Project identifier Deutsche Forschungsgemeinschaft (DFG) - Project number 165937581
 
This research project deals with the development of a holistic 3D-FEM-simulation model to assess the component quality influenced by the interactions of process and machine. Based on the simulation methodology developed in the initial application, it is now possible to extend the simulation model to internal broaching. At the begin, experimental studies aiming at analyzing the production process as well as finally validating the simulation model to be developed will be conducted. For this aim, the impact of minor cutting edges on process forces is evaluated by conducting tests with single-cutting tools in full section and comparing the force evolution to the values of the specific process forces. In a further step, the analytical model for predicting the specific process forces is extended by the cross force component to be able to calculate all the forces acting. This is necessary, since the work up to was focussed on external broaching and the production process was simulated with orthogonal cutting. To be able to replicate the machine dynamics as accurately as possible, it must be experimentally investigated how the machine interacts with the built-in internal broaching tool and the clamping of the workpiece. The machine model will be set up and validated. In the following work package, the machine model will be linked with the analytical model for calculating the specific forces. The coupling of the two models will take place at two interfaces: tool-process and process-workpiece. Afterwards, the developed simulation model will be validated with and if necessary adapted to the data generated in the first work package. In conclusion, the developed simulation methodology will be applied exemplarily to another production process in order to evaluate the methods adaptivity.
DFG Programme Research Grants
 
 

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