As an alternative to powder-bed based processes, metal parts can be additively manufactured by extrusion based additive manufacturing. In this process, a highly filled polymer filament is deposited and subsequently debindered and sintered. Choosing a proper orientation of the part that satisfies the requirements of the debinding and sintering processes is crucial for a successful manufacturing process. To determine the optimal orientation for debinding, first, the part must be scaled in order to compensate the sinter induced shrinkage. Then, a finite element analysis is performed to verify that the maximum stresses due to the dead load do not exceed the critical stress limits. To ease this selection process, an approach based on open source software is shown in this article to efficiently determine a part’s optimal orientation during debinding. This automates scaling, debinding simulation, and postprocessing for all six main directions. The presented automated simulation framework is examined on three application examples and provides plausible results in a technical context for all example parts, leading to more robust part designs and a reduction of experimental trial and error. Therefore, the presented framework is a useful tool in the product development process for metal extrusion additive manufacturing applications.

High-performance computing (HPC) enables both academia and industry to accelerate simulation-driven product development processes by providing a massively parallel computing infrastructure. In particular, the automation of high-fidelity computational fluid dynamics (CFD) analyses aided by HPC systems can be beneficial since computing time decreases while the number of significant design iterations increases. However, no studies have quantified these effects from a product development point of view yet. This article evaluates the impact of HPC and automation on product development by studying a formula student racing team as a representative example of a small or medium-sized company. Over several seasons, we accompanied the team, and provided HPC infrastructure and methods to automate their CFD simulation processes. By comparing the team’s key performance indicators (KPIs) before and after the HPC implementation, we were able to quantify a significant increase in development efficiency in both qualitative and quantitative aspects. The major aerodynamic KPI increased up to 115%. Simultaneously, the number of expedient design iterations within one season increased by 600% while utilizing HPC. These results prove the substantial benefits of HPC and automation of numerical-intensive simulation processes for product development.

Hemming is a mechanical joining method that is typically used to connect two sheet metal components, such as inner and outer panels of automobile doors or hoods. Hemming generates defects like outer sheet size reduction (called roll-in), cracks and sheet metal springback. This affects the final dimensions of the hemmed part and can cause problems in the assembly stage or damage the product appearance. Hemming process control is currently experience-oriented and die design is based on trial-and-error. Therefore, developing predictive modeling capability and establishing die and process design guidelines are helpful to a better process understanding and control. FE simulations of the hemming process are realized at PSA Peugeot Citroën with the explicit code OPTRIS using under-integrated shell elements. Whereas they give a good estimation of the roll-in for steel sheets, the estimation is inaccurate for aluminum sheets. The article describes an analytical model and an implicit FE-model based on plane strain elements (FORGE2 ® ). The simulations are applied to an aluminum sheet assumed to be isotropic with an isotropic hardening law determined from tensile tests. The results given by the analytical model and the FE-codes are then compared to the experimental observations. The element types as well as the material models used are then discussed and evaluated. Solutions for improving the hemming modeling are finally proposed.