激光选区熔化关键工艺参数对热物理过程的影响

Influence of Critical Process Parameters on the Thermal Physical Process in Selective Laser Melting

激光选区熔化(selective laser melting,SLM)采用激光束将金属粉末等分层熔融成形,在制造业中具有重要价值。然而成形过程中的热物理现象及各工艺参数对热物理过程的影响有待进一步研究。在综合考虑SLM成形过程中材料相变、粉体—实体不可逆转变等过程的基础上,建立了SLM成形316L不锈钢的多道扫描温度场数值模拟模型。研究了激光功率、扫描速率和激光束有效直径对SLM温度场、熔融时间、冷却速率和熔池尺寸等的影响,并通过实验验证了数值模拟结果的可靠性。结果表明:熔融时间易受激光功率和扫描速率的影响,而最大冷却速率更易受激光束有效直径的影响。激光功率较低或扫描速率较大时,熔池尺寸较小,易形成孔穴类缺陷;激光束有效直径对熔池尺寸影响较小。随着激光功率增加,熔池稳定性先无确定变化趋势后增加;随着扫描速率增加,熔池稳定性不断降低;激光束有效直径对熔池稳定性的影响不确定。实验结果与数值模拟分析结果基本一致,研究结果可为SLM工艺参数调整与优化提供参考。

Selective laser melting(SLM)is of vital value in the manufacturing industry which melt powder material,such as metal powder,layerby-layer by using laser beam.Nevertheless,the thermal physical phenomena and the influence of process parameters on the thermal physical process need to be further studied.A multi-track numerical model,considering the phase change and irreversible powder-to-solid transition,was established to simulate the SLM of 316L stainless steel.The effects of laser power,scan speed and effective laser beam diameter on the temperature field,melting time,cooling rate and melt pool dimension was studied.Experiment was conducted to verify the reliability of numerical simulation results.The results indicated that the melting time is easily affected by laser power and scan speed,while the maximum cooling rate is more sensitive to effective laser beam diameter.With relative low laser power or high scan speed,the melt pool dimension is comparatively small,and easy to form cave like defects.The effective laser beam diameter has a small effect on the melt pool dimension.The stability of melt pool firstly has no certain change tendency and then increases with the increasing laser power.With the increase of scan speed,the stability of melt pool decreases continuously.The effect of effective laser beam diameter on the stability of melt pool is uncertain.The numerical simulation results are approximately in accordance with the experimental results and provide guides to tuning and optimizing the process parameters in SLM.