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Knowledge base for intelligent press hardening

Wissensbasis für ein intelligentes Presshärten
 
: Landgrebe, Dirk; Pierschel, Norbert; Schönherr, Julia; Polster, Stefan; Priber, Ulrich; Schieck, Frank

International Deep Drawing Research Group -IDDRG-; Chinese Academy of Science, Institute of Metal Research -IMR-:
IDDRG 2015, the 34th International Deep Drawing Research Group Conference. Proceedings : May 31 - June 3, 2015, Shanghai, China
Shanghai, 2015
pp.404-413
International Deep Drawing Research Group (IDDRG Conference) <34, 2015, Shanghai>
English
Conference Paper
Fraunhofer IWU ()
hot forming; 22MnB5; simulation; process control; knowledge base

Abstract
Today, a continuously increasing complexity of equipment and processes characterizes the production technologies. This also applies to press hardening, a hot sheet metal forming process, by that car body components with a high crash performance at low weight can be produced. The control of the press hardening process is challenging due to its complexity, the large number of parameters and their correlations as well as the need for user knowledge. However, it is in terms of an economic and sustainable process essential to correct any process variations within a very short time in order to ensure a consistent part quality and thus avoid waste.
In this paper the results of an AiF / EFB-funded project are presented in which a concept for intelligent process control in press hardening was developed. The scientific basis is a sensitivity analysis using FEM, which analyzes relevant process parameters such as sheet thickness, transfer time or strain rate in terms of their influence on key quality parameters of the component. By that, essential process parameters with significant impact on quality-related outcomes, such as the springback, thinning and the hardness profile in cross-section of the component were determined, evaluated and modeled mathematically. The FEM results, causal relationships and mathematical models were then integrated into a knowledge base. This makes use of meta-models and enables to link the input variables (influencing factor) with the output parameters (command variable) under defined preconditions. Using the example of the production of a sill geometry the created concept of a process control was successfully implemented. With an extensive monitoring and control-related coupling of systems (forming press, handling systems, heating furnace, etc.) an exact recording of the process parameters was possible. Based on this, during the press hardening process a comparison of the measured process variables took place with the knowledge base and thus the component quality expected was predicted. De-pending on the technological feasibility a controlled process, which means the adjustment of process parameters for the currently in process component, was implemented. The components produced were then tested for their mechanical and geometrical properties assigned to each process variable combinations and evaluate the results against the command variables. Thus, the project makes a significant contribution to the science-based description of the press hardening process and ist influencing factors, for the collection of expert knowledge and implementation of the findings in a knowledge base that allows an intelligent process control.

: http://publica.fraunhofer.de/documents/N-379635.html