Real-time process control of powder bed fusion by monitoring dynamic temperature field

This study aims to optimize the uniformity of the temperature field during sintering to improve part performance.A temperature-field monitoring system is established based on an infrared thermal imager and the temperature field data obtained during the sintering of a part can be measured in real time.The relationship among the sintering temperature field,sintering process parameters,and part performance is established experimentally.Subsequently,a temperature field monitoring and analysis system is constructed,and various sintering temperature-field control strategies are established for various part sizes.Finally,a dynamic control strategy for controlling the temperature field during sintering is proposed,experimentally validated,and fully integrated into a developed powder bed fusion(PBF)equipment.For eight-shaped standard parts,the range of sintering temperature field is optimized from 44.1℃to 19.7℃,whereas the tensile strength of the parts increased by 15.4%.For large-size H parts,localized over burning is eliminated and the final quality of the part is optimized.This strategy is critical for the optimization of the PBF process for large-sized parts,in particular in the large-sized die manufacturing industry,which offers promise in the optimization of part performance.

High-accuracy calibration for multi-laser powder bed fusion via in situ detection and parameter identification

Multi-laser powder bed fusion(ML-PBF)adopts multiple laser-scanner systems to increase the build envelope and build speed,but its calibration is an iterative and time-consuming process.In particular,multiple large-scale scan fields have a complex distortion in the overlap area,challenging the calibration process.In this study,owing to the enormous workload and alignment problems in the calibration of multiple scan fields,a novel calibration system is designed in this study to realize in situ auto-detection of numerous laser spots in the build chamber to ensure high efficiency and accuracy.Moreover,because the detectable area could not cover the entire build area and the detection data still contained errors,a virtual laser-scanner system was established by identifying the assembly defects and galvo nonlinearities of the ML-PBF system from the detection data,which served as the system's controller to improve calibration accuracy.The multi-field alignment error was less than 0.012%,which could avoid the intersection and separation of scan paths in multi-laser scanning and therefore meet the requirements for high-precision ML-PBF.Finally,the reliability of the method was verified theoretically using principal component analysis.