|Theme||Forming technology, Industry 4.0, Artificial Intelligence|
|Project title||Design of efficient forging sequences with mass distribution around the center of gravity line for forging parts (Effiziente Stadienplanung)|
|Project duration||01.11.2017 – 31.01.2021|
To increase the economic efficiency in the production of geometrically complicated forgings, material efficiency is a determining factor. For a high degree of material utilization, the preforms are decisive, which can be designed using efficient planning of process chains and preform geometries.
The aim of the project is to develop a universal method for process-reliable planning of multi staged forging sequences for forgings of all kinds. Based on a CAD geometry, the method should determine the resulting center of gravity line (3D) and mass distribution of the workpiece. Starting from the finished forging, the mass distribution is to be approximated to the mass distribution of the bar stock. The method considers forming rules in order to develop the forging sequence.
This method saves enterprises time in the development of the forging sequence. Furthermore, it is possible to increase the material efficiency in the production process by using the method.
Publications about the project
This paper presents a method for the automated classification of forged parts for classification into the Spies order of shapes by artificial neural networks. The aim is to develop a recognition program within the framework of automated forging sequence planning, which can directly identify a shape class from the CAD file of the forged part and characteristics of the forged part relevant for the design of the process.
Material efficiency and the development time of a forging sequence are decisive criteria for increasing the economic efficiency in the production of complex forgings. SMEs can often only interpret forging sequences in a shortened form due to insufficient capacities and high competitive pressure. Therefore, a generally valid method is to be developed that automatically generates multi-stage, efficient forging sequences based on the mass distribution of any forged part.
automated process design, die forging, resource efficiency