Effect of Layer Time Control via Physics-Based Model on Layer Temperature in Extrusion-Based Large Format Additive Manufacturing

Abstract

Abstract In polymer extrusion-based large format additive manufacturing (AM), the strength and structural integrity of printed parts depend on interlayer bonding, which is highly affected by layer temperature. Layer deposition with an improper layer temperature can result in undesirable defects such as warping, cracking, and debonding. A critical factor in this layer deposition process is the layer deposition time, commonly known as “layer time,” which significantly impacts layer temperature and interlayer bonding strength. For example, an excessively long layer time results in an over-cooled surface, leading to interlayer debonding, cracking, and warping. Conversely, an excessively short layer time causes overheating, leading to material collapse due to insufficient stiffness when new layers are deposited. Traditionally, layer time have been determined based on the experience of skilled operators, employing a fixed rate throughout the entire printing process. This approach often fails to address dynamic changes during the printing process. Furthermore, it is limited by the absence of comprehensive guidelines based on accurate data and systematic analysis. Determining the best optimal layer time is further complicated by the influence of variable environmental conditions, geometric complexities, and printing parameters. There exists a clear need for a layer time control framework that can determine the best optimal layer time to achieve the desired layer temperature across all deposited layers, ultimately leading to an optimal printing outcome. In response to these challenges, a finite element analysis (FEA) model was used to simulate the additive deposition process. After the deposition of each layer, the simulation process paused, and the temperature data was fed into the previously developed layer time optimization framework. With the optimization framework, an optimal layer time for each successive layer was determined based on the cooling behavior of previously deposited layers. By updating the layer time based on the results from the optimization framework, the FEA model continued the deposition process continuously. The layer temperature is adjusted with the adaptive layer time control process. By implementing this approach, a mismatch between the target temperature and the simulated layer temperature was reduced from 27.8% to 4.7% for the second layer. In addition, the mismatch for the third layer was reduced from 11.7% to 0.3%. We aim to illuminate the influence of layer time control on layer temperature during polymer extrusion-based large format AM. This research will contribute to the advancement of realtime control systems in large format AM.