Feedback control in deep drawing based on experimental datasets

5Citations
Citations of this article
17Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

In large-scale production of deep drawing parts, like in automotive industry, the effects of scattering material properties as well as warming of the tools have a significant impact on the drawing result. In the scope of the work, an approach is presented to minimize the influence of these effects on part quality by optically measuring the draw-in of each part and adjusting the settings of the press to keep the strain distribution, which is represented by the draw-in, inside a certain limit. For the design of the control algorithm, a design of experiments for in-line tests is used to quantify the influence of the blank holder force as well as the force distribution on the draw-in. The results of this experimental dataset are used to model the process behavior. Based on this model, a feedback control loop is designed. Finally, the performance of the control algorithm is validated in the production line.

Cite

CITATION STYLE

APA

Fischer, P., Heingärtner, J., Aichholzer, W., Hortig, D., & Hora, P. (2017). Feedback control in deep drawing based on experimental datasets. In Journal of Physics: Conference Series (Vol. 896). Institute of Physics Publishing. https://doi.org/10.1088/1742-6596/896/1/012035

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free