News Archive
Illinois Awarded a DMLM Additive Manufacturing System from GE
September 6, 2018 GE Additive concluded the 2018/19 cycle of its Additive Education Program (AEP) by announcing that the University of Illinois at Urbana-Champaign is one of five universities in Europe and the United States that will receive a Concept Laser Mlab 200R direct metal laser melting (DMLM) additive manufacturing system.
Virtual Supply Chain Creates Digital Twin for Simulations and Optimization
June 14, 2018 The Applied Research Institute has partnered with Mechanical Sciences and Engineering at Illinois and Digital Manufacturing Design (DMDII) to develop an Operating System for Cyberphysical Manufacturing (OSCM).
ICRT finds simple solutions to indoor air quality
June 12, 2018 Researchers in the Illinois Applied Research Institute ‘s Indoor Climate Research & Training (ICRT) division have completed a field study to better understand the indoor air quality (IAQ) impacts of having an attached garage and how to best minimize the consequences.
ARI, team seek to improve corrosion prevention treatments
June 12, 2018 Corrosion remains a crucial problem to the Department of Defense (DoD). It costs the DoD $22.9 billion annually based on 2010 data and weighs on the global economy as a whole.
ARI manages summer internship program with Sandia National Laboratories
June 12, 2018 As a part of the continued alliance between the Sandia National Laboratories (SNL) in Albuquerque, New Mexico, and the University of Illinois at Urbana-Champaign, ARI managed a summer internship pilot project through Sandia's internal funding sources.
Software development looks to provide tools for cancer detection
June 12, 2018 The Illinois Applied Research Institute (ARI) has partnered with the University of Illinois Chemical Imaging and Structures Laboratory (CISL) to develop image processing software tools for cancer detection in human tissue samples.
ARI develops sensor-agnostic model to measure track uncertainty
June 12, 2018 The defense and intelligence communities have a lot of interest in accurately tracking vehicles and dismounts. While there are many tracking algorithms for a variety of sensors, there has been little research into measuring the inherent uncertainty of tracked trajectories and how to combine these trajectory uncertainties with other sensor information.