Analysis of 3d printing process parameters for mechanical properties and fatigue behavior of specimens produced by bound metal deposition of 17-4 PH stainless steel

Abstract

3D printing—a state-of-the-art additive manufacturing technology—has revolutionized the production of intricate andnovel structures. The qualityof these structureslargely depends on the various printingparameters and the properties of material of interest. Manufacturers often conduct several trial-error processes for choosing the optimizedprinting parameters, thus makes 3D printing processes expensive, time consuming and challenging. The objective of the current study was to optimize the ultimate tensile strength, fatigue behavior and amount of material required considering a set of key process parameters for a standard specimen made of 17-4 PH stainless steel. This study has considered four key printing parameters, such aslayer height, build orientation, infill pattern and infill percentage, for the chosen specimen.Finite element analysis was conducted to ascertain the tensile strength and fatigue cycle whereas slicing software was employed to assess filament length in the printed specimen.The response surface methods were used to develop design of experiments and this resulted in 117 experimental runs. The investigation has consideredmaximizing tensile strength, minimizing material consumption, and maximizing fatigue cycles as objectives of optimization. The significance of printing parameters was evaluated through analysis of variance, main effect, and interaction plots.Three separate predictive models were developed for optimized value of ultimate tensile strength, filament length, and fatigue behavior. The optimum levels of the process parameters were calculated as 87% infill percentage, 0.6 mm layer height, honeycomb infill pattern, and on-edge build orientation. The study concludes thatthe infill percentageshows the greatest effect on the tensile strength, filament length, and fatigue cycle, howeverthe infill pattern shows the trivial impact.It is expected that the understanding of the parameter optimization of 3D printing structureswill contribute to the development of metal 3D printing technology.