Yorck Hedicke-Claus

Graduation:
M.Sc.
Function:
Project engineer
Practice Areas:
Computer-aided preforming optimization, process design
Phone:
+49 (0)511 279 76-343
E-Mail:
hedicke-claus@iph-hannover.de
vCard:
vCard

Publications

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.

forging, ANN,CAD

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

Research projects

Job offers