Fatigue properties and S-N curve estimating of 316L stainless steel prepared by SLM

•DMS-PSO algorithm was first introduced to optimize the parameters of three parameter Weibull distribution model.•The effectiveness of the fatigue life prediction based on three-parameter Weibull distribution model by the DMS-PSO algorithm was proved.•Weibull distribution model was applied in the fatigue-life curves estimation of SLM316L, the S-N curves were highly consistent with the of metallographic and fractographic phenomena.•DMS-PSO algorithm can improve the stability and accuracy of optimization in three-parameter Weibull distribution model. This paper investigates the fatigue properties of 316L stainless steel manufactured by selective laser melting technology (SLM) under hot-isostatic-pressing (HIP) heat-treatment. The fatigue tests of 316L specimens were carried out under pulse tensile cyclic loading to obtain the fatigue performance. To avoid falling into local optima and improve the convergence speed, the dynamic multiswarm particle swarm optimizer (DMS-PSO) algorithm was first introduced for parameter optimization of the three-parameter Weibull distribution model, and then the S-N curves based on the model were obtained. The S-N curves were highly consistent with the metallographic and fractographic phenomena. Besides, both the S-N curves and fractographic analysis show that the resistance of high-stress fatigue fracture is significantly improved by using HIP heat-treatment.