VoKoES

Predicting and compensating for part distortion caused by residual stresses occurring during 5-axis machining operations

Funding agency

Sponsored as EFRE-0801656 / MP-2-2-039e by

European Regional Development Fund
EFRE NRW

Details

Producing companies in the metal processing industry are subject to the highest requirements with regard to high component quality and low manufacturing costs. A frequently occurring problem that has not been mastered so far is component distortion due to internal stresses during 5-axis milling. This distortion reduces the manufacturing accuracy, often causes time-consuming and cost-intensive reworking of the component and causes frequent rejects.

The research project “VoKoES” enables the prediction and compensation of component distortion due to residual stresses during 5-axis milling and in CAM programming. For this purpose, the project is divided into four sub-goals. In the first step a simulation for the determination of residual stress states in semi-finished products is developed. Then an algorithm for FEM simulation of component distortion during 5-axis milling is developed. These two sub-goals enable the prediction of component distortions and are coupled in the project. The third sub-goal is the development of methods to compensate for component distortion during 5-axis milling, which are based on the previously developed prediction methodology. Finally, in subgoal four, an adaptive clamping system for the detection and relaxation of component distortion will be developed. Finally, the researched compensation methods will be implemented in a CAM module. The algorithms developed by ModuleWorks for machine and material removal simulation as well as ModuleWorks’ experience in these areas form the basis for this. During the development of the “StockManager” product, our development teams have already gained extensive experience in the management of digital representations of current machining progress. 

VokoEs

Partners

Project start: Jul 2019

Project end: Jun 2022

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