Date: February 14, 2020
Time: 1:00 pm
Location: CHBE Room 102
Discovery Through Process Data Analytics
Process plants may have thousands of measurements. They also have intricate connections that mean the measurements are not independent of one other. The talk will describe research that has helped with the complicated challenges of generating insights from these measurements to improve process performance. As an example, Prof Thornhill will show how data analytics revealed the widespread consequences of compressor recycling on a North Sea oil and gas platform.
She will give some opinions about how process data analytics fit into the wider context of autonomous operation and artificial intelligence, and will speculate about research trends in the next few years.
Nina Thornhill is a professor in the Department of Chemical Engineering at Imperial College London, where she has held the ABB Chair of Process Automation since 2007. Her interests are industrial automation and data analysis with applications in oil and gas, chemicals, and electricity transmission. She graduated with BA in Physics from Oxford University in 1976, MSc from Imperial College in Control Systems in 1983, and (part-time) PhD from UCL in 2005. Previous positions include ICI for six years, and E&E Engineering Department at UCL from 1984 to 2007. She undertakes industrial secondments whenever possible, including a Royal Society Industry Fellowship with BP from 1992-4, and with ABB in Poland from 2017-9.