Closed-Loop-Regelung eines virtuellen Umformprozesses

• Forschungsstelle: COST
• Projektnummer: C00.0081
• Projekttitel Englisch: Closed-Loop-Regelung eines virtuellen Umformprozesses

Schlüsselwörter (Englisch)

Mdelling; process optimization; neural networks

Forschungsprogramme (Englisch)

COST-Action P4 - Non-linear dynamics in mechanical processing

Kurzbeschreibung (Englisch)

See abstract

Weitere Hinweise und Angaben (Englisch)

Full name of research-institution/enterprise: Fachhochschule für Technik St. Gallen

Partner und Internationale Organisationen (Englisch)

CZ, DK, F, D, GR, H, IRL, I, NL, PL, SI, E, S, CH, GB

Abstract (Englisch)

To optimise a production process is a difficult, expensive, time-consuming and sometimes dangerous procedure - especially if more than 2 or 3 process parameters are involved or if the process is non-linear. In practical applications this procedure is often carried out on a trial-and-error basis. More systematic Design of Experiment methods do exist, but the practitioner most often considers them as too expensive and too rigid. In this project the optimisation of a metal forming process is considered in order to investigate the optimisation methodology. A cylindrical piece of steel is is deformed in a press, with length, diameter and thickness of the deformed piece as product properties. The crucial question in process optimisation is: Which process parameters lead to a product with the desired product properties? This question should be answered with as few experiments as possible. On order to minimize costs, a first optimisation phase is carried out virtually. The production process is substituted by a Finite Element calculation. Even on a powerful computer a single FE-calculation takes several hours. Since the optimisation requires several hundred calculations, a less time consuming model is required. Adaptive Neuro-Fuzzy Inference Systems, trained with the results of a number of FEM-calculations, turned out to mimic the FE calculation successfully. Since a recall of a small neuro-fuzzy inference system takes in the order of milliseconds these systems are apt for integration in a real-time optimisation loop. It could be shown that with 3 input dimensions 30 virtual experiments are sufficient to find the desired operating point - significantly less than with classical Design of Experiments methods.

Datenbankreferenzen (Englisch)

Swiss Database: COST-DB of the State Secretariat for Education and Research Hallwylstrasse 4 CH-3003 Berne, Switzerland Tel. [phone] Swiss Project-Number: C00.0081