Abstract
Heavy asset industries generate a huge amount of data from equipment sensors at their plants or on their fleets. Relatively recently the application of machine learning techniques to these data, with the aim of improving and automating operations, has become a fast growing field of interest. I will present some of the unique opportunities, challenges and technologies encountered in the data science process from raw industrial data to actionable insights using real world examples from the oil & gas, mining, maritime and utility industries.
Speaker Bio
Mark is a data scientist in Arundo Analytics’ Oslo office where he has a core role in advanced analytics engagements with partner organizations and researchers. His current focus is around IIoT data analysis for industries such as oil & gas, mining, maritime and utilities. He previously worked as a postdoctoral researcher at Berkeley National Laboratory where he had a leading role in analysing data from the Large Hadron Collider facility at CERN. Mark obtained a PhD specializing in High Energy Physics from Imperial College in 2010.