ABSTRACT

On Dec 5, 2022, researchers of the National Ignition Facility at Lawrence Livermore National Lab conducted a first-time-ever controlled nuclear fusion experiment in which the fusion energy output was 1.5 times greater than the laser energy input. The success of this landmark experiment made headlines to all major news outlets and was hailed as a step forward in the development of clean, fusion-powered generators which may one day meet the world's energy needs without producing harmful wastes and emissions. Important to the success of this fusion experiment is to polish the fuel capsule to nanometer precision. This talk, based on three journal articles published in ASME Journal of Manufacturing Science and Engineering and IISE Transactions, respectively, recounts how engineering data science contributes to decision makings in the ultraprecision polishing process.

BIO

Dr. Yu Ding is the Anderson-Interface Chair and Professor in the H. Milton School of Industrial and Systems Engineering at Georgia Tech. Prior to joining Georgia Tech, he was the Mike and Sugar Barnes Professor of Industrial and Systems Engineering at Texas A&M University. Dr. Ding's research is in data and quality science and system informatics. He is the author of the CRC Press book, Data Science for Wind Energy and a co-author of the Springer Nature book, Data Science for Nano Image Analysis. His research work is recognized by the 2019 IISE Technical Innovation Award and 2022 INFORMS Impact Prize. Dr. Ding is a Fellow of IISE and ASME, and is serving as the Editor-in-Chief of IISE Transactions for the term of 2021-2024.