Identification of the Optimal Blank Holder Force through In-Line Measurement of Blank Draw-In in a Deep Drawing Process

Abstract

During the forming process, variations in noise parameters can negatively impact product quality. To prevent waste from these fluctuations, this study suggests a method for the in-line optimisation of the deep drawing process. The noise parameter considered is the friction coefficient, assuming the variability in lubrication conditions at the blank–tool interface. The proposed approach estimates the noise factor variability during the process by tracking the draw-in of the blank at critical points. Using this estimation, the optimal blank holder force (BHF) is calculated and then adjusted in-line to modify blank sliding and prevent critical issues on the component. For this purpose, a Finite Element (FE) model of a deep drawing case study was developed, and numerical simulation results were used to construct surrogate models while estimating both the friction coefficient and optimal BHF. The FE model’s predictive capability was verified through preliminary experimental tests, and the control logic was numerically validated. Results show the effectiveness of this control type. By adjusting the BHF just once, a defect-free component is achieved. This method overcomes the limitations of feedback controls, which often need multiple adjustment steps. The time required to estimate the friction coefficient and the maximum time available for adjusting the BHF without causing defects was identified.

Keywords

• deep drawing
• draw-in
• blank holder force
• industry 4.0
• surrogate model
• in-line control