Sciaky joins the Alliance for the Development of Additive Processing Technologies
March 13, 2019
Sciaky’s EBAM systems can produce parts ranging from 203 mm (8 in) to 5.79 m (19 ft) in length (Courtesy Sciaky, Inc.)
Sciaky, Inc., Chicago, Illinois, USA, a subsidiary of Phillips Service Industries, Inc., (PSI) and leading provider of metal Additive Manufacturing solutions, has joined the Alliance for the Development of Additive Processing Technologies (ADAPT) to expand the adoption of its Electron Beam Additive Manufacturing (EBAM®) technology in aerospace and other sectors.
Headquartered at Colorado School of Mines in Golden, Colorado, USA, ADAPT is an industrial-academic consortium that aims to advance data informatics and characterisation technologies to optimise processes, materials, and parts for Additive Manufacturing. One of the barriers to AM process qualification which ADAPT will reportedly work on in collaboration with Sciaky is the lack of fundamental understanding about how process variables affect material microstructure and final part properties.
“Sciaky is pleased to work with the innovators of this higher learning consortium,” stated Scott Phillips, President and CEO of Sciaky, Inc. “We are always striving to break new ground with our EBAM process, as well as capture critical performance data on new applications.”
Sciaky’s EBAM systems can produce parts ranging from 203 mm (8 in) to 5.79 m (19 ft) in length. EBAM is also said to be the fastest deposition process in the metal AM market, with gross deposition rates ranging from 3.18 to 11.34 kg (7–25 lbs) of metal per hour.
The company’s systems also offer its Interlayer Real-time Imaging and Sensing System (IRISS®) for quality control, said to be the only real-time adaptive control system in the metal AM market that can sense and digitally self-adjust metal deposition precisely and reliably. This closed-loop control is said to enable the Sciaky’s EBAM to deliver consistent part geometries, mechanical properties, microstructures, and metal chemistry across a batch of parts.
