America Makes, the National Additive Manufacturing Innovation Institute that’s focused on helping the U.S. grow capabilities and strength in 3D printing, has recently awarded $540,000 to General Electric and Lawrence Livermore National Laboratory(LLNL) for development of open-source algorithms that will improve additive manufacturing (3D printing) of metal parts.  

The project intends to develop and demonstrate software algorithms that will allow selective laser melting (SLM) to produce metal parts that are high quality and durable.

SLM is a metal powder-based, additive manufacturing process where a 3D part is produced, layer by layer, using a focused, high-energy laser beam to fuse the metal powder particles together.

Currently, there is no common approach to SLM that comprehensively reduces problems associated with this method such as surface roughness, residual stress, porosity and micro-cracking. Without careful optimization of the process, these issues may cause parts to fail.


Creating robust, reliable 3D-printed parts

“With the SLM processes in place now, you don’t always end up with a part that is structurally sound,” said Ibo Matthews, a researcher with LLNL’s Accelerated Certification of Additively Manufactured Metals (ACAMM) Strategic Initiative team who is leading the Lab’s effort on the joint project. “It’s critical to have mechanically robust parts, especially for applications in industries such as aerospace and energy, where part failure could lead to major problems.”

To print a 3D part using the SLM process, the user must enter data into the printer using a stereolithography (STL) file, which is a digitized 3D representation of the desired build.

“Ideally, you would send the STL file to an arbitrary 3D printer and it will print out parts that are consistent in terms of dimensions and material properties,” Matthews said. “Currently, that doesn’t happen.”

That’s partly because errors appear during the initial translation of the STL file, requiring the user to fill in missing information as well as specify the type of powder material used. To further complicate matters, traditional printer designs treat every layer of powder the same, without giving consideration to the thermal properties of the powder. Some printer systems provide more control than others.

In an ideal system, different layers would demand different laser scanning speeds and powers because the powder environment is changing as the layer-by-layer buildup proceeds.

“Commercial SLM machines do not permit access to specific process parameter information and tool paths,” said Bill Carter, a researcher with GE’s Additive Manufacturing Lab, which is under GE’s Global Research. “This limits the ability of researchers to perform controlled validation experiments that support modeling work and process development.

Matthews said: “If you were able to process a 3D part by telling the machine what are the right laser parameters, then the overall manufacturing process can be made more robust and efficient.”

Leveraging the capabilities of Lawrence Livermore’s High Performance Computing and its expertise in lasers, Matthews and his GE colleagues are developing software algorithms that will be compatible with all 3D printers that produce metal parts, optimizing the heating and melting for each layer by controlling the scan laser’s parameters, such as beam size, scan rate and power, on the materials, its powder characteristics and the detailed shape of the part being printed.

“There are a number of SLM machines out there,” Matthews said. “But there isn’t a common software that allows them to produce standard parts that are consistent in terms of material properties.”

Because the software will be available to the public, Matthews hopes it will lead to more breakthroughs in the AM industry.

“If we can lower the barriers to entry, we can help U.S. companies, universities and research labs make further advances in additive manufacturing,” he said.

GE and LLNL are tasked by America Makes to develop the software algorithms in the next 18 months. LLNL researcher Gabe Guss is also working with GE and Matthews on the project.

Image credit:  Lawrence Livermore National Laboratory
Via Kurzweilai