Project funding
Project partner
Background
Additive manufacturing is becoming increasingly important as the individualization of products progresses. The laser powder bed fusion process (PBF-LB/M, or SLM for short) plays a decisive role in the production of complex geometries. The time-consuming development of individual tools is no longer necessary, which means that the process enables comparatively cost-effective production from a batch size of one. Three-dimensional components with an almost arbitrary shape can be produced through targeted exposure of the metal powder. The cohesion of the metal particles is achieved by short-term, selective melting using highly coherent laser light.
Problem statement
In additive manufacturing, the aim is usually to achieve a maximum material density of 100% in order to come as close as possible to the condition of a rolled or forged material. A major problem in achieving this goal is the formation of process-related pores and bonding defects, which impair the component density and the static and dynamic strength to varying degrees. The process errors are based on different, sometimes complementary, complex mechanisms that cannot be controlled and influenced by today's machine controls in additive manufacturing.
Goals
The aim of the research project is to develop a self-adapting control system that determines ideal production parameters depending on relevant process and measurement variables. The adaptation of the laser power and scanning speed parameters is realized by integrating a separate control system into a classic SLM machine. The system will be equipped with the necessary sensors by the project partner, the Materials Testing Institute (MPA) at the University of Stuttgart, to detect relevant process and measurement variables. A data-driven model will ensure that optimum process conditions are guaranteed at runtime, thereby increasing the resulting component quality. The validation of the process optimization through metallurgical tests is carried out by the MPA.
Get in touch
David Hecht
M.Sc.Research Assistant "Mechatronic Systems and Processes"