Session Title: Moving from Periodic Preventive to Condition Based Predictive Maintenance Utilising More Process and Device Big Data
Abstract TBC
Moderator: Troy Stewart, Head of Oil, Gas and Chemicals Service, UK ABB
1545-1615: Reducing Deferment with Predictive Data Analytics
Sankesh Sundareshwar, Senior Process Engineer Shearwater, Shell UK
Abstract:
Unintended loss of uptime (trips) in gas compression systems is one of the top causes for unscheduled deferment across Shell operated ventures. Causes for compressor failures could be attributed to lack of or inappropriate maintenance, incorrect operating practices and integrity issues, as identified in the Oil and Gas UK compressor study. The focus of this presentation is on compressor systems in production facilities that have major production deferments associated with them. Shell is developing and deploying machine learning models to determine anomalous behaviour and predict potential “trip” conditions and probable root cause with sufficient warning times to allow for intervention.
1615-1645: Reduced Maintenance Cost By Using Process Data, Failure Mode Analytics and Condition Monitoring For Planning of Maintenance Services.
Espen Storkaas, Group Vice President, ABB
1645-1715: Discussion with the presenters / Q&A Panel:
Data driven analytics versus deterministic approach