Automated Simulation of Selective Laser Melting Additive Manufacturing for Process Design

Additive Manufacturing (AM), where three-dimensional (3D) objects are created from a digital model by depositing and fusing successive layers of material, provides the ability to produce low-volume, customized products with complex geometries relatively quickly at a moderate cost. However, AM processes sometimes fail to produce acceptable parts, due to either geometric in- accuracy (e.g., shrinkage or warping) or unacceptable material properties, and it is not currently possible to determine a priori whether a process will fail or not. This significantly increases the costs associated with using AM. The overall objective is to develop automated simulation tools for modeling AM processes that accurately predict part geometry and state, such as residual stresses, porosity, and microstructural features related to part quality, for given AM processing conditions, with a focus on Selective Laser Melting (SLM). Such a simulation capability would allow AM system developers and users to try proposed process plans in simulation first. We also plan to develop inverse methods and control strategies using the simulation tools for process design and control. While the pro- posed project will develop tools for SLM, the basic architecture can be extended to a larger family of AM processes. Commercial Applications and Other Benefits: This project will produce an advanced simulation system for modeling AM processes that will allow AM equipment manufacturers to produce better systems, increasing the efficiency and reducing the cost of AM. The core technologies developed in this project will be general and will be applicable for use with a wide variety of applications, thus providing benefits past AM applications. Simulation is widely used in the design processes of a large number of industries, including aerospace, electronics, energy, biomedical, and consumer goods; the core tools that Simmetrix provides are already advancing industrys ability to perform predictive analysis and design for complex engineering systems in a time- and cost-effective manner.