This presentation was held at the 2020 NAFEMS UK Conference "Inspiring Innovation through Engineering Simulation". The conference covered topics ranging from traditional FEA and CFD, to new and emerging areas including artificial intelligence, machine learning and EDA.

Resource Abstract

This project presents a Discrete Element Method (DEM) simulation of an Additive Manufacturing (AM) process and introduces a complete workflow of creating virtual materials that replicate the real powders and analysis of particle data through continuum fields. This work is a collaboration between the commercial code EDEM, created by DEM Solutions Ltd, and the Barnes Group Advisors, who are experts in the field of AM.

The handling of bulk solids, in the form of powders, is a fundamental process in a wide range of manufacturing industries. Some of these industries include the automotive, aerospace, and healthcare sectors that employ AM. AM includes various manufacturing processes that enables users to produce complex parts in a short amount of time. Thus, considered an established method to developing an agile manufacturing environment, that can drastically reduce the lead time from conception to the production stage.

Different types of powders are the main material used in these AM processes and they are fed into various AM production equipments through delivery systems. The latter uses a prescribed volume of powders and controls its flow into the printers spreading systems, hence dictates the success or failure of the end product and influences the machine set-up needed. Furthermore, it is critical to understand the effect of powder properties on the mechanics of the system and optimise the equipment. Due to the sensitivity of powder properties to environmental and machine conditions, it is not straight-forward to determine what the optimal configuration may be. Consequently, trial-and-error testing, plus a reliance on know-how from previous work is often the method. This results in extension of the overall part production cycle, as well as increased cost.

This work presents a simulation of an experimental dosing system using DEM and employs the coarse-grained approach to extract continuum fields from discrete data. Specifically, DEM is used to create a set of virtual materials that mimic the behaviour of two different powders through suitable characterisation tests and simulates the entire dosing processes to insure systematic delivery. The powders are modelled using a meso-scopic modelling approach to insure practical computational time, while taking into consideration the particle size and shape. Bi-sphered particles with aspect ratio of 1.25 are used to capture the effects of particle non-sphericity on the bulk behaviour of the material. The Edinburgh Elasto-Plastic Adhesion (EEPA) contact model was used to model the virtual particle interaction in order to capture the complex elasto-plastic-adhesive behaviour of powders. Furthermore, continuum descriptions have been very successful in describing the macroscopic physical behaviour of discrete systems, hence this approach is used herein to investigate the behaviour of the discrete materials by using continuum fields, like density, momentum, velocity and temperature.

Fine powders are particularly challenging with complex elasto-plastic-adhesive behaviour that produce unwanted agglomeration phenomena hindering their flow. At the same time performing experiments is challenging due to the opaque nature of the system making. The methodology presented herein provides deep understanding of the mechanics of such solids, making such simulations an indispensable tool for complex industrial applications.