Data-driven software analyzes the relationships between additive manufacturing process parameters and material performance
NEW YORK, N.Y.—Senvol has publicly announced that it is developing data-driven machine learning additive manufacturing (AM) software for the U.S. Navy’s Office of Naval Research (ONR). Senvol’s software analyzes the relationships between AM process parameters and material performance.
The ONR’s goal is to use Senvol’s software to assist in developing statistically substantiated material properties in hopes of reducing conventional material characterization and testing that is needed to develop design allowables.
“We are very excited about our work with the Navy’s Office of Naval Research,” Senvol President Annie Wang said in a press release. “Our software’s capabilities will allow ONR to select the appropriate process parameters on a particular additive manufacturing machine given a target mechanical performance. This presents a unique opportunity to reduce the high level of trial and error that is currently required, which would save a tremendous amount of time and money.”
Wang said that in addition to its machine learning capabilities, Senvol has also developed a computer vision algorithm that analyzes, in real-time, in-situ monitoring data. “This enables us to detect irregularities in real-time and begin to quantify the relationships between irregularities in the build and the resulting mechanical performance,” she said.
A modularized ICME (integrated computational materials engineering) probabilistic framework for AM data serves as the foundation for Senvol’s software. In this framework, AM data is categorized into four modules: Process parameters, process signatures, material properties, and mechanical performance. The software being developed is powered by an algorithm that quantifies the relationships between the four modules. The algorithm is AM material- ,machine- , and process-agnostic.
The development is being funded through Navy Phase II STTR N16A-002.
The software under development will be made commercially available to any company looking to qualify AM parts. Companies that are interested in potentially gaining beta access to the software can contact Senvol at firstname.lastname@example.org for more details.
Senvol (http://senvol.com) will be presenting on its work at several upcoming conferences, including Rapid + TCT (April), and CAASE18 (June).