Robers, Maarten; DEKRA; Netherlands
Robers, M.; DEKRA; Netherlands
Session: Structural Health Monitoring 1
Time: 13:30 - 13:50
Condition monitoring is disrupted by predictive analytics, big data and Industrial IoT propositions for asset management. These new technologies will eat a chunk of today’s NDT market. In many cases they can increase productivity and plant reliability while reducing safety hazards for onsite technicians and the environment.
Over time these technologies will find a place in everyday processes and installations. The visionary customers of today’s proof-of-concept and pilot projects will be followed by pragmatists that require ease of implementation, reliability and a clear return on investment.
Integration of the new technologies in existing processes and with existing techniques could be crucial for broader application. This requires combining the various sources of condition monitoring data into a (predictive) model or representation. Which is to be done in a way that supports decision-making in the operation, maintenance or asset management process in general. Permanently installed sensors (like a UT wall thickness sensor) and existing process or maintenance related data will be some of these sources of data. Non-standardized NDT sensors may find easier application in such an integrated model as they can be applied based on their merits while other data sources compensate for the shortcomings. Even manual NDT could still be applied to fill in particular gaps or build confidence. Choosing the most effective sources of data or measurement positions requires specific NDT expertise.
The key challenge for an integrated approach lies in the cooperation between NDT companies, new technology suppliers and the owner/operator of the plant. This goes beyond the departments within the organization that are traditionally involved in NDT. IT and ERP system owners for instance may need to provide access to their area. When the cooperation runs smoothly the end result will benefit of the specific capabilities of each party in the evolving asset management ecosystem.