Abstract

Powder flowability is a critical parameter for additive manufacturing techniques involving powders. In order to obtain thin and homogenous powder layers, a compromise between grain size and flowability has to be found. Unfortunately, when the grain size decreases, the cohesiveness increases and the flowability decreases. Too often, both the powder spreadability assessment and the optimization of printing parameters are costly empiric processes. In this paper, we describe an original method associating GranuDrum powder flow characterization instrument and DEM numerical simulations to asses the process-ability of powders and to optimize printing parameters like recoater speed, layer thickness or recoater geometry. The powder characterization allows to calibrate the simulation parameters and in particular to quantify the inter-grain cohesiveness. Then, the recoating process is simulated with the calibrated simulations to predict the behaviour of the powder inside the printer. In parallel, the results are validated by testing the powder in a printer equipped with an in-situ powder layer homogeneity tester based on image analysis.

Abstract

Additive Manufacturing (AM) has been a subject of significant attention from both industrial manufacturers and research communities. However, several challenges hinder the widespread implementation of this technology in the industry. Powder recoating is a crucial step in powder-bed AM process that involves achieving a uniformly packed bed of powder particles that are later melted by an energy source, such as a laser or electron beam. One of the main challenges is calibrating the contact model parameters accurately to match the flowability and spreadability of specific powder alloys. This paper proposes a Discrete Element Method (DEM) model calibration framework based on surrogate model optimisation. The study utilises a Revolution Powder Analyser (RPA) as the experimental reference system. The proposed method is demonstrated with two AM powder samples, Ti64 and Inconel 718. The results indicate that particle-particle friction, rolling resistance, and van der Waals (vdW) surface energy significantly affect the system responses. Furthermore, the validation results show good correspondence between the simulation with calibrated parameters and experimental data. Overall, proposed calibration framework has the potential to optimise powder recoating and to improve the accuracy and effectiveness of the additive manufacturing.