Simulation Mechanism Development for Additive Manufacturing

Selective laser melting process is an emerging additive manufacturing technology with promising presence in the medical ( orthopaedics) industry as well as in the aerospace, high technology engineering and electronics sectors. Published literature shows that past research has been focused mainly on additive manufacturing of high quality parts depending on correct selection of material parameters, laser parameters for each point exposure and correct orientations of the part and its supports. However, there is a pressing need to simulate the build chamber of a selective laser melting machine, so that a close enough approximation of the actual build process could be obtained. In the present work, a number of experiments have been conducted to study the chamber atmosphere variability inside the build chamber during vacuum creation and inert/breathing cycles. Effect of other devices such as wiper, elevator, pumps andvalves are also studied. The obtained experimental data has been utilised to derive regression equations correlating the chamber pressure and oxygen levels with chamber build times under different conditions of peripheral devices. Subsequently, these equations were modelled to obtain the simulation model. Confirmation experiments were carried out to validate the simulation results. This work enables the end user to view the real time simulation of vacuum creation and inert gas environment building process. Values of parameters such as build chamber pressure, oxygen levels and conditions of other devices can be seen in real time. Thus, the developed simulation saves precious time and resources of an additive manufacturing user and enables him to make an informed decision by providing him the exact parameter values suitable for his manufacturing needs. (C) 2017 Elsevier Ltd. All rights reserved. Selection and Peer-review under responsibility of the Committee Members of International Conference on Advancements in Aeromechanical Materials for Manufacturing (ICAAMM-2016).