A Comparative Study on the Effects of an Advanced Scan Pattern and Intelligent Scan Sequence on Thermal Distribution, Part Deformation, and Printing Time in PBF Additive Manufacturing
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引用次数: 0
Abstract
Parts made using powder bed fusion (PBF) additive manufacturing often suffer from deformation, residual stresses, cracks, and other defects stemming from non-uniform thermal distribution during the printing process. Scan pattern (i.e., the geometric pattern of an infill) and scan sequence (i.e., the order in which features of a geometric pattern are scanned) are among the approaches that have been explored to achieve more uniform thermal distribution and reduce thermally-induced defects. The authors have recently proposed an intelligent approach (called SmartScan) for generating scan sequences. SmartScan is model-based and optimization-driven. However, it has only been applied to the most rudimentary scan patterns. This paper compares the separate and combined effects of an advanced scan pattern (the varying-helix pattern) and SmartScan on thermal distribution, part deformation, and printing time in PBF additive manufacturing. Simulations and experiments involving laser marking of AISI 316L stainless steel plates are employed for the comparison. Using SmartScan applied to a rudimentary pattern as a benchmark, the experimental results demonstrate that the application of the advanced pattern without SmartScan improved both temperature uniformity and reduced deformations by 20%, at the cost of 7% increase in printing time. The combination of the advanced pattern and SmartScan yielded 28% and 33% improvement in thermal uniformity and reduction in deformation, respectively, at the cost of 18% increase in scanning time.
期刊介绍:
The Journal of Micro and Nano-Manufacturing provides a forum for the rapid dissemination of original theoretical and applied research in the areas of micro- and nano-manufacturing that are related to process innovation, accuracy, and precision, throughput enhancement, material utilization, compact equipment development, environmental and life-cycle analysis, and predictive modeling of manufacturing processes with feature sizes less than one hundred micrometers. Papers addressing special needs in emerging areas, such as biomedical devices, drug manufacturing, water and energy, are also encouraged. Areas of interest including, but not limited to: Unit micro- and nano-manufacturing processes; Hybrid manufacturing processes combining bottom-up and top-down processes; Hybrid manufacturing processes utilizing various energy sources (optical, mechanical, electrical, solar, etc.) to achieve multi-scale features and resolution; High-throughput micro- and nano-manufacturing processes; Equipment development; Predictive modeling and simulation of materials and/or systems enabling point-of-need or scaled-up micro- and nano-manufacturing; Metrology at the micro- and nano-scales over large areas; Sensors and sensor integration; Design algorithms for multi-scale manufacturing; Life cycle analysis; Logistics and material handling related to micro- and nano-manufacturing.