SPE NE TechTalk Series | Industrial Internet of Things (IIoT) in Oil Industry | by Endress+Hauser |

In today's process automation plants, many field devices and sensors from various manufacturers are installed and used. To operate these plants economically, a successful Plant Asset Management is necessary to optimize the maintenance and servicing of these assets. Studies have shown that up to 70% during a maintenance job is spend with the search for information - not with the actual maintenance job. With the possibilities available today for the digital documentation of assets, this effort can be drastically reduced. This not only increases the efficiency of the maintenance technicians, but also reduces the risk of faulty / inefficient maintenance, as the correct information is provided to the right person.

However, the core requirement is a well-maintained and comprehensive device information database, which usually must be created. The biggest obstacle to the creation and introduction of such a device information data-base is the collection of the device data itself: existing documentation about installed devices is often outdated or not complete, so that this can hardly serve as a basis. There is usually no other way than to go through the system physically, to manually identify, capture, and create the database. Obviously, this method of creating the database presents a great deal of time and personnel. In addition, neither the data consistency nor the actuality of the data is guaranteed.

With regards to industry 4.0 and the associated digitalization, the presentation will show a way to create a device database fully automatically – vendor independent. This device database in combination with the now established connectivity lays the foundation for further use cases. Starting from the live health of the connected devices, predictive maintenance use cases are now reality.

The presentation will demonstrate how the database is generated, what technical pre-requisites are necessary, how asset health and predictive maintenance are currently implemented. Technologies to retrieve data from instrumentation, suitable for greenfield as well as brownfield installations, will be highlighted as well.