Industrial servo presses have been used to successfully demonstrate improved formability when deforming sheet metals. While the time dependent viscoplastic behavior of material is attributed to the observed formability improvement, much less effort has been devoted to understand and quantify the underlying mechanisms. In this context, the hole expansion test (HET) of a dual phase steel was interrupted at pre-defined punch travel heights to understand the time-dependent effects on stretch-flangeability. The effect of pre-strain, hold time and edge quality on hole expansion ratio (HER) improvement was studied. The present study shows that the HER improves significantly in interrupted HET. This improved HER is due to the combined effects of stress relaxation and friction on deformation behavior. The ductility improvement estimated from uniaxial stress relaxation tests was used to estimate the contribution of stress relaxation and friction, respectively, in HET. This study shows that friction plays a significant role in improving HER at high pre-strain. It was also demonstrated that frictional effects are largely influenced by edge quality.

The increasing growth of digital technologies in manufacturing has provided industry with opportunities to improve its productivity and operations. One such opportunity is the digital thread, which links product lifecycle systems so that shared data may be used to improve design and manufacturing processes. The development of the digital thread has been challenged by the inherent difficulty of aggregating and applying context to data from heterogeneous systems across the product lifecycle. This paper presents a reference four-tiered architecture designed to manage the data generated by manufacturing systems for the digital thread. The architecture provides segregated access to internal and external clients, which protects intellectual property and other sensitive information, and enables the fusion of manufacturing and other product lifecycle data. We have implemented the architecture with a contract manufacturer and used it to generate knowledge and identify performance improvement opportunities that would otherwise be unobservable to a manufacturing decision maker.