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Unmanned and Autonomous Systems: Future of Automation in Process..

Unmanned and Autonomous Systems:

Future of Automation in Process and Energy Industries'' by Dr. Mehmet Mercangöz

 

 

 

Abstract

Process and energy industries have been recognized as adopters of high levels of automation compared  to other sectors. Nonetheless, human cognitive input still plays a critical role in the operation of process  plants and the replication of these cognitive capabilities via algorithms and computational methods  remains a challenge. In this talk, we will go over an analysis of process plants based on a scenario of  reduced availability of skilled labor and increased demands for safety, sustainability, and resilience.  We will look at the various tasks involving mechanical labor, sensory effort, situational awareness,  and decision-making in the operation of process plants and map them to possible realizations of  unmanned and autonomous systems. We will discuss the factors influencing complexity of operation  in process plants and how complexity can be linked to automation challenges. We will also discuss  the importance of human-machine collaboration and the different types of interaction humans and  autonomous systems can have in a process plant setting. As part of autonomous system capabilities,  we will consider adaptation as a key capability and we will make a connection to adaptation of model based solutions. Lastly, we will assess current technology capabilities and provide some perspectives  for future technology development. The closing argument will be that reaching higher and wider levels  of autonomy requires a rethink of the design processes for both the physical plants as well as the way  automation, control, and safety solutions are conceptualized. 

Biography

Dr. Mehmet Mercangöz is recently appointed as the ABB  Reader in Autonomous Industrial Systems at the Department  of Chemical Engineering of Imperial College London. Since  2018, he also holds an appointment at ETH Zurich as a  Lecturer at the department of Information Technology and  

Electrical Engineering. Previously, he served for 14 years at  the Corporate Research Organization of the company ABB,  most recently as a program manager for industrial artificial  intelligence. From 2012 to 2018 he led the control and  optimization research group in Switzerland. His research  spans the fields of model predictive control, machine  learning, and process optimization. He has worked on  

electrical variable speed drives for natural gas compressors  as an emission free alternative for gas turbine drivers. The control solutions he helped develop for  these applications are now responsible for the safe delivery of natural gas to many European countries.  He previously worked in the development of energy storage applications based on thermodynamic  cycles and on manufacturing such as pulp and paper production. Dr. Mehmet Mercangöz received his  B.Sc. and M.Sc. degrees from Boğaziçi University, İstanbul, Turkey, in 2000 and 2002, respectively  and his Ph.D. degree from the University of California, Santa Barbara, CA, USA, in 2007, all in  Chemical Engineering.


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