Industry 4.0 and Smart Predictive Maintenance

PhD Candidate Tom Ivar Pedersen

Main Supervisor Per Schjølberg

Sponsor: Lundin Energy Norway AS

Recent developments in sensor technology combined with improvements in systems for collecting, storing and analyzing large amounts of data, often associated with the term Industry 4.0, are expected to bring substantial changes to how maintenance and asset management will be conducted in the upcoming years. One example of this is predictive maintenance which has the potential to reduce maintenance costs by allowing maintenance organizations to focus resources on the right equipment at the right time, and improve safety and availability by reducing the level of unplanned corrective maintenance. Outcome of the project: Methods and models that explore how digital solutions can be used to improve the economic value generated from a production asset.

Project result: Predictive maintenance on centrifugal pumps 
A study case predicting remaining useful life using head degradation data which allows to plan timely maintenance operations considering uncertainty