Senvol
Senvol ML software in use
Senvol has announced that it has received funding from the U.S. Army to lead a program focused on demonstrating that consistent part performance can be achieved on different additive manufacturing machines located at different sites.
The program was created with the goal of accommodating the reduction of cost and lead time of Army ground vehicle systems while increasing performance. Senvol will use its 3D printing machine learning software, Senvol ML, to reduce the cost of material and process development and to enable the Army to produce AM parts of consistent performance, even when using different systems at different sites according to the company.
The program is titled “Applying Machine Learning to Ensure Consistency and Verification of Additive Manufacturing Machine and Part Performance Across Multiple Sites”, and commenced in March 2023, running through March 2025.
Aaron LaLonde, PhD, Technical Specialist – Additive Manufacturing at the U.S. Navy said: “For additive manufacturing to be successfully implemented into the Army’s supply chain, it is essential to be able to produce parts of consistent performance even if different machines are used at different locations. Today, that is much easier said than done. During this program, we are pleased to work with Senvol to demonstrate the use of its machine learning technology to aid in achieving what everyone in the additive manufacturing industry strives for, a truly flexible supply chain.”
According to Senvol, the approach demonstrated in the program will be able to be applied to any AM process, any AM material, and any AM machine. The company also says it will develop and validate an approach that can be used to continue to verify AM machine and part performance when there are changes to a process, for example when a new powder supplier is used.
The program will involve Senvol ML being used to develop process parameters and establish a process model for different AM machines located at different sites. The software will also be used to quantify complex and interdependent PSPP relationships.
Senvol President Zach Simkin added: “Consistency, or lack thereof, is a problem that nearly everyone in the additive manufacturing industry can relate to. The Army, and DoD in general, has been at the forefront of tackling pressing issues in our industry, and we are pleased to work with them again to demonstrate the use of our machine learning software as a mechanism to ensure consistent part performance across different sites and machines.”
Senvol has been involved with the defence sector in the past, in 2020, the US Air Force deployed Senvol ML to assist with a multi-laser 3D printing program. The program, called FlexiSpecs, was a collaborative effort between the Air Force Research Laboratory (AFRL) and the Air Force Life Cycle Management Center (AFLCMC) focused on developing methodology to demonstrate the airworthiness of an EOS M400-4 quad-laser metal 3D printing system.
