SC Solutions’ Nathan Rogers Invited to Speak at the SmallSat Symposium in Silicon Valley
SC Solutions’ Senior Analyst Nathan Rogers was invited to share his experience and perspective at the 2023 SmallSat Symposium. He will be giving a technical brief on the importance of structural engineering in today’s evolving space industry on February...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...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].