Feedback control in deep drawing based on experimental datasets

Abstract

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.

Methodological approach for the development of an operator assistance system for the press shop

“…6-10) is significantly higher than on the left side (pos. [16][17][18][19][20] and leads to necking. Differences can also be observed between positions 3 and 13.…”

“…Recently, however, optical measurement systems have been preferred, although there is a risk of contamination by oil or dust, which may lower their operational suitability. Camera-based systems are able to capture the skid-line distance to the part flange [15] as well as the local material flow [16] and allow the measurement of the global blank draw-in [17] or at least large parts of the global blank draw-in [18]. While these systems are only able to detect the final state of the drawn part and neglect the draw-in curve, laser displacement sensors can overcome this shortcoming and may be an alternative [13].…”

On part-to-part feedback optimal control in deep drawing

“…The advantage of the experimental based approach is that it is not influenced by the unknown accuracy of the finite element simulation and is only influenced by the accuracy of the measurement system and the repeatability of the process. The number of experiments usually has to be kept as small as possible in order to minimise disruption to the production line, so the identification of the Jacobian can be either determined by carrying out a full experiment design, as done by Fischer [22], or by using a reduced design which only varies each actuator on its own. The full design has the advantage of the possibility of determining the Jacobian inside the design space, while the reduced version is more cost effective.…”

“…The virtual validation of the approach is carried out using two different demonstration parts. The first demonstration part is the kitchen sink described by Fischer [23], while the second part is a front fender which is mentioned in Fischer [22].…”

“…In addition to testing the control approaches on simulation based models, the controller was also tested on the experimentally generated models described by Fischer [22]. The controller uses sensors three and four (figure 14), as they show the best predictions of the draw-in and the controllers based on these two measurements worked well.…”