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Condition-based Survey

The Lifecycle Approach to Survey

Survey after construction has been on an evolutionary path within the marine and offshore industry via digitalization and the large-scale use of data.  The last 20 years have seen advances in how the surveys are conducted based on the actual condition of the asset and issues specific to vessel types and age, along with the condition of protective coatings, corrosion levels, and equipment-condition monitoring playing a role.

Digitalization and the tools used to collect, store, and analyze the mass of data streaming from assets will play a role in improving their integrity and performance with a new lifecycle approach that is more vessel specific, condition-driven, and continuous.  Surveys will be informed by various data-driven approaches, specifically:

  • Structural survey will be guided by historical data compiled from the vessel’s operational profile itself.  Load and damage accumulation exposure based on real-time AIS route and weather data information will help characterize structural risk, with added sensor based systems of varying degrees helping to inform and calibrate the above approaches.  A surveyor will better understand how to survey that vessel, not only based on a prescriptive rule-set but based on the actual vessel history itself. Such information will also factor into advanced survey-planning via the use of drone and robotic technologies. 
  • Machinery surveys will evolve as health monitoring techniques reach new levels of capability and proficiency in the age of smart equipment. Techniques employing comprehensive solutions to real-time health and performance monitoring will become the norm. Such approaches will employ comprehensive solutions involving traditional condition monitoring techniques, as well as both physics-based and analytics-based composite models. The use of data analytics (covering the application machine learning and artificial intelligence), will augment the traditional approaches and help owners better utilize operational data to help diagnose deficient conditions and also provide prognosis the time to take corrective action.  
  • Aiding the survey in all aspects above will be the data infrastructure necessary to put this information at the attending surveyor’s fingertips. Mobile and augmented reality technology will also enable desktop SME support as well as putting the health status and data-driven knowledge into a practical view to help inform the survey execution.        

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