SC Solutions joined SEMI and participated in the Global Smart Manufacturing Conference — GSMC, November 8-10, 2022
SC Solutions, a leader in providing advanced sensing, control, and signal processing solutions to the semiconductor industry, recently became a member of SEMI, the global industry association serving the product design and manufacturing chain for the electronics...APCSM Conference at Austin, TX, October 10-13, 2022
SC Solutions was again a sponsor for the annual Advanced Process Control Smart Manufacturing (APCSM) Conference and gave an in-person presentation there on the application of Digital Twins technology to semiconductor wafer processing. The APCSM conference, which was...Modeling the Seismic Response of Spent Nuclear Fuel in Dry Storage
The US Department of Energy’s Spent Fuel and Waste Science and Technology (SFWST) program is investigating the mechanical loading of spent nuclear fuel (SNF) to close knowledge gaps and inform the range of relevant loads for mechanical testing of irradiated SNF. The...Physics-informed Machine Learning for Control – DNN in a Dynamic Feedback Loop
This Case Study describes an approach to combining physical principles with Machine Learning (ML) for modeling and control of complex systems. Our approach was developed as part of a DARPA-funded research project. It was applied to oil reservoir management. While this Case Study provides an overview, technical details may be found in a separate publication [1].