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Publication

Tuning Process Parameters and Polymer Powder Formulation for Laser Sintering

Book - Dissertation

Additive Manufacturing (AM), popularly known as 3D printing, is a novel group of technologies to manufacture geometrical complex parts without the need for dedicated tooling. The market of AM technologies and products has seen a consistent growth and expansion into new applications. Laser Sintering (LS) is one of the AM techniques that makes use of a laser to selectively fuse a preheated bed of thermoplastic polymer powder. Researching the Laser Sintering process parameters for specific polymers is important to expand the number of available materials and their performance. The large number of tunable parameters results in a tedious and iterative development and optimization of polymer grades, often following a trial-and-error approach. This work aims to identify and apply more rigorous approaches to tailor and optimize conventional engineering polymers to the required physical material characteristics for Laser Sintering. To support the investigations in this thesis, the methods for determining powder characteristics and thermal behaviour that are relevant for Laser Sintering and give indication of successful processing are discussed. These characteristics direct the development of polymer powder grades and the optimization of process parameters such as the powder bed temperatures and the laser parameters. In the development of polymer grades for LS, the temperature window is the interval between the onset of melting and the onset of crystallization temperature. This temperature window indicates the required temperature of the powder bed. The laser parameters are most commonly optimized using the laser energy density, an engineering parameter that includes laser power, scan speed and hatch spacing. The first two investigations focus on non-semicrystalline thermoplastic polymers. They do not show a distinct temperature window and gradually soften with increasing temperature. The study of the surface roughness of single layers demonstrates a method to determine the powder bed temperature and laser energy density for an amorphous thermoplastic polystyrene. This study also reveals the importance of particle size in determining optimal process parameters. The gradual softening of non-semicrystalline thermoplastics limits the powder layer deposition at the elevated temperatures in the LS building chamber. Therefore, an amorphous polystyrene and a thermoplastic polyurethane elastomer powder are formulated with additives to improve powder flow. The investigated additives are silica flow agent and carbon black. Higher powder bed temperatures are achievable upon addition of the flow additives, although the coalescence of the powder particles after laser exposure is reduced. The third investigation looks into processing high-temperature engineering thermoplastics. The higher melting temperature of these polymers requires a higher bed temperature and thus processing in a dedicated high-temperature LS system. By using a matrix/filler approach, this requirement can be circumvented. A polyamide-12/polyamide-4,6 is investigated as a proof of principle for this approach, where the polyamide-12 is a matrix material that has a temperature window achievable in conventional LS machines, and the polyamide-4,6 acts as a non-melting filler. The final investigation makes use of the Buckingham-Pi theorem of dimensional analysis as an approach to link the material properties and process parameters such as the powder bed temperatures and laser parameters. The statistical analysis of two designs of experiments that make use of the dimensionless Pi-groups, shows that the thermal window for powder bed temperature and the laser energy density are not exhaustive as optimization variables. To extend LS parameter optimization to other materials and machines, key material characteristics (the specific enthalpy of heating and melting and powder bed density) and key machine characteristics (laser spot size) are essential.
Publication year:2020
Accessibility:Open