Additive manufacturing for mass oroduction: a new model to estimate the crystallinity and tensile properties of polypropylene by multi-jet fusion

Powder bed fusion (PBF) is an important additive manufacturing (AM) technology that is widely implemented to rapidly fabricate high-precision metallic, polymeric, ceramic, and composite components. The build time for PBF-based manufacture, however, remains extensive. To address this issue, recently high-speed sintering PBF processes, such as HP’s Multi-Jet Fusion (MJF™) technology, were developed to produce polymeric components with much higher throughput. The crystallinity and mechanical properties of components fabricated with MJF™ and other PBF technologies will depend on both process parameters and thermoplastic polymer solidification and crystallization properties. In this research, a new mathematical model has been developed to estimate the crystallinity of semicrystalline polypropylene based on MJF™ process parameters. The proposed predictive model for the crystallinity is a function of the temperature of the process and subsequently the process parameters such as tool power, tool speed, and the scanning area. In addition, an empirical model is also described, which links the crystallinity to the tensile properties of the printed structures quantitatively. The model was validated by the experimental results from mechanical testing and differential scanning calorimetry (DSC). The results from this study demonstrate the precision of the proposed model in predicting both the crystallinity and mechanical attributes of MJF™-printed polymeric materials, which can be used to accelerate design and process optimization for AM production and elevate its acceptance and integration in mainstream engineering.