• PT Youtube
  • PT Facebook
  • PT Linkedin
  • PT Twitter
3/15/2018 | 1 MINUTE READ

Senvol Developing Data-Driven Additive Manufacturing Software for U.S. Navy

Facebook Share Icon LinkedIn Share Icon Twitter Share Icon Share by EMail icon Print Icon

The software under development will be made commercially available to any company looking to qualify AM parts.

Senvol is a New York-based company that develops database and additive manufacturing (AM)-related software and data sets. The company recently announced it is developing data-driven machine learning 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. 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.

Senvol President Annie Wang says that the company’s software’s capabilities will allow ONR to select the appropriate process parameters on a specific 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,” she says.

Wang continued, “In addition to our machine learning capabilities, we have 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.”

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.

RELATED CONTENT


Related Topics