Advanced experimental and numerical methods for the analysis of the dynamic forming press behavior. - Peter Groche; Knut Großmann; Thomas Hofmann; Hajo Wiemer (Prod. Eng., 2007)

Prediction and inline compensation of springback in roll forming of high and ultra-high strength steels. - Peter Groche; Philip Beiter; Michael Henkelmann (Prod. Eng., 2008)

Process control at the sealing line during sheet metal hydroforming. - Peter Groche; Metin Ertugrul (Prod. Eng., 2008)

Determination of material properties for hot hydroforming. - D. Elsenheimer; Peter Groche (Prod. Eng., 2009)

Experimental and numerical investigation of the hydroforming behavior of paperboard. - Peter Groche; D. Huttel; Paul-Philipp Post; S. Schabel (Prod. Eng., 2012)

Numerical analysis of the potential of deep drawing processes with hydrostatic pressure lubrication. - Peter Groche; Christian Klöpsch; Norman Möller (Prod. Eng., 2012)

Statistical analysis of a model based product property control for sheet bending. - Peter Groche; Stefan Calmano; Tina Felber; Sebastian O. Schmitt (Prod. Eng., 2015)

Examination of tailored preforms produced by rotary swaging for subsequent hydroforming. - Peter Groche; Falko Vogler; Lennart Wießner (Prod. Eng., 2015)

Surface pre-treatment and its influence on electric functionality and the formability of screen printed steel sheet. - Peter Groche; Annemie Kleemann; Stefan Köhler 004 (Prod. Eng., 2018)

Identification of Model Uncertainty via Optimal Design of Experiments applied to a Mechanical Press. - Tristan Gally; Peter Groche; Florian Hoppe; Anja Kuttich; Alexander Matei; Marc E. Pfetsch; Martin Rakowitsch; Stefan Ulbrich (CoRR, 2019)

Workpiece Image-based Tool Wear Classification in Blanking Processes Using Deep Convolutional Neural Networks. - Dirk Alexander Molitor; Christian Kubik; Ruben Helmut Hetfleisch; Peter Groche (CoRR, 2021)

Sensor Integrated Load-Bearing Structures: Measuring Axis Extension with DIC-Based Transducers. - Nassr Al-Baradoni; Peter Groche (Sensors, 2021)

Smart sheet metal forming: importance of data acquisition, preprocessing and transformation on the performance of a multiclass support vector machine for predicting wear states during blanking. - Christian Kubik; Sebastian Michael Knauer; Peter Groche (J. Intell. Manuf., 2022)

Tool Wear Segmentation in Blanking Processes with Fully Convolutional Networks based Digital Image Processing. - Clemens Schlegel; Dirk Alexander Molitor; Christian Kubik; Daniel Michael Martin; Peter Groche (CoRR, 2023)