Abstract

During the transition from the melt into the solid phase semi-crystalline thermoplastics form crystalline regions. The amount of the crystals and their grow rate depend on the material properties and the cooling conditions. These regions significantly change the mechanical and technical properties, such as stiffness, elongation or chemical resistance, of a component. Knowledge about the degree of crystallization (fraction of crystalline regions) resulting from a manufacturing process can therefore help to better predict and evaluate the component properties obtained. Furthermore, the influence of process parameters on the degree of crystallization can be investigated and experimental effort can be reduced. The calculation of the degree of crystallization is shown here on the example of the additive manufacturing process Filament Fuse Fabrication (FFF). In this process, a polymer melt is deposited through a nozzle and the component is created layer by layer. In additive manufacturing with its complex cooling conditions, the degree of crystallization influences not only the material properties but also the component properties, such as the bonding (inter layer strength). The aim is to apply a known crystallization model to the example of AM optimized PEEK. The model is implemented in Abaqus, in order to be able to predict the degree of crystallization of semi-crystalline thermoplastics, based on the existing temperature conditions in the FFF process. Since crystallization depends on many process and material parameters, the prediction of crystallization kinetics is quite complex. The approach chosen is based on a formula that is a further development of the Avrami approach. In addition to temperature-time data, this also includes parameters determined by fitting differential scanning calorimetry (DSC) curves. DSC measurements with different cooling rates are considered. By using the different DSC data, the cooling rate dependent degrees of crystallization can be calculated. A Python script for fitting the parameters of semi-crystalline thermoplastics is developed, various fitting strategies are tested and rising problems are discussed. The resulting crystallization model is applied to a simplified 2D model of an FFF process. Individual beads are considered, which are activated sequentially to model the deposition process. Individual thermal boundary conditions are set for each activation step to model the cooling as accurately as possible. The effects are discussed and modelling recommendations derived.