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基于正交试验法的热冲压SDCM钢渗氮工艺优化 被引量:5

Nitriding Process Optimization of Hot Stamping SDCM Steel Based on Orthogonal Experiment
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摘要 通过设置不同的渗氮时间(8h、12h、16h)、温度(500℃、530℃)、气压(380Pa、480Pa)以及气体比(8∶1,6∶1/NH3∶Ar)等工艺参数来对热冲压SDCM钢进行离子渗氮实验。并通过对表面硬度、化合物层厚度、渗氮层深度、表面脆性、脉状组织评级以及表层物相组成等实验结果采用正交分析的方法确定出SDCM钢的最佳渗氮工艺。在实验结果优化分析过程中,表面硬度及脆性、脉状组织评级以及表层物相组成等实验结果的重要程度高于化合物层厚度和渗氮层深度。首先对每组试验结果进行单独的评级优化,然后综合不同实验结果的重要程度,通过正交分析中的直观分析方法来确定出SDCM钢最优的离子渗氮工艺。优化结果表明,在渗氮时间为12h,温度为530℃,压力为480Pa以及气体比为6∶1的工艺下SDCM钢渗氮层深度为300μm左右,白亮层厚度在7μm左右,表面硬度为1090HV,韧性相含量为51.2%,表面脆性较好没有出现渗层剥落的现象,此外,扩散层中只有少量细小的脉状组织出现。 The hot stamping SDCM steel was ion nitride under different parameters including time (8 h, 12 h, 16 h), temperature (500 ℃, 530 ℃), air pressure (380 Pa, 480 Pa) and gas ratio (NHa : Ar was 8 : 1,6 : 1). By determing the surface hardness, compound layer thickness, the depth of the nitrided layer, surface brittleness, vein structure rating and surface sediments of the phase composition, the optimum working conditons were determined by using the orthogonal analysis method. The experimental results of the surface hardness and brittleness, vein structure rating and surface sediments phase composition higher than the thickness of the compound layer and the depth of the nitrided layer. First of all, each goals (above aims) was optimized, separately. Then all the goals optimized together, considering the priority of the goals, through the orthogonal analysis of the intuitive analysis method to determine the optimal SDCM steel ion nitriding process. The optimization results were obtained at 6 : 1 gas mixture ratio, at the temperature of 530 ℃, at the pressure of 480 Pa and for 12 h process time. which nitriding depth at 300μm, compound layer at about 7μm, surface hardness at 1090HV, ductile phase content was 51.2% and the spalling of surface layer brittleness was not obvious,in addition, only a small amount of fine vein structure appeared in the diffusion laver.
出处 《材料导报(纳米与新材料专辑)》 EI 2016年第2期590-596,共7页
关键词 热冲压SDCM钢 离子渗氮 正交优化 hot stamping SDCM steel ion nitriding orthogonal optimization
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