Dr. Bin Shams: Big Data Analysis Helps in Fault Detection and Diagnosis in Chemical Processes

Dr. Mohammed Ali Bin Shams, Associate professor of Chemical Engineering at the University of Bahrain, said that data analytics improves downstream operations by detecting faults in chemical processes, which would contribute to the achievement of ‘safe and economically feasible operations.’

In his paper entitled, ‘Fault Detection and Diagnosis in Chemical Processes Using Big Data Analysis,’ Dr. Bin Shams said that the digital transformation at both the technical and support operational levels has created a valuable resource of data. He suggesting processing this large amounts of data using advanced analytics which would achieve operational excellence in refining.

The paper was presented at the recent GDA International Downstream Conference & Exhibition 2018. This year’s theme was, “Towards a Competitive Downstream through Innovation, Collaboration and Technology.”

The GDA Conference 2018 was organized by the Gulf Downstream Association (GDA) in collaboration with the National Oil and Gas Authority (NOGA). Executive heads, engineers and researchers from major oil companies in the region participated in the conference, including Saudi Aramco, Bahrain National Oil Company (Bapco), Kuwait Petroleum Corporation (KPC) and Abu Dhabi National Oil Company (ADNOC). The Conference took place at the Bahrain International Exhibition & Convention Centre on the 23rd – 25th October.

Dr. Bin Shams’ paper focused on the current digital infrastructure of refineries and its impact on the transformation of the relationship between human factors and the surrounding industrial environment, such as the operating equipment, measurement and control devices, and databases across the production chain. It also shed light on the importance of utilizing Big Data analytics in both the refining and manufacturing industries to obtain tangible economic results through the convergence of IT and operational technology.