Ying Lin, Ph.D., an Assistant Professor in the Industrial Engineering Department at the Cullen College of Engineering, has received a grant from the Advanced Manufacturing Institute at the University of Houston to improve the uniformity of long-length high temperature superconductor tapes during superconductor manufacturing process.
Lin collaborates with two UH colleagues on this project – Qianmei (May) Feng, Ph.D., Professor in the Industrial Engineering Department; and Wenjiang Fu, Ph.D., Professor of Statistics and Director of the Statistics and Data Science Program at the College of Natural Sciences and Mathematics.
According to Lin, High Temperature Superconductor (HTS) tapes have the potential to provide multiple commercial solutions to a broad spectrum of sectors of the US economy such as energy, defense and medicine. However, it is challenging to achieve uniform performance over long-length HTS tape due to the unstable manufacturing process.
To help achieve the uniformity in-field performance of superconductor manufacturing, Lin and her team will develop novel machine learning techniques to discover the critical process parameters affecting the uniformity of superconductor tapes. They will also provide real time monitoring to better control the manufacturing process, and collaborate with the experts of superconductor manufacturing in AMI and apply their techniques to the AMI’s pilot-scale superconductor manufacturing process.
Lin also serves as the director for the Smart Health & INtelligent Engineering Systems (SHINES) Lab at UH. Research interests of the SHINES Lab lie at the interactions of data analytics, quality engineering and healthcare. Feng and her research lab studies quality and reliability problems for complex systems.