Eigen Ingenuity Digital Twin
The Digital Twin capability in Eigen Ingenuity is powered by the Data Model (also called Asset Model); a contextualised digital map of your information showing where it is and how it is related. In some cases it may also contain the information itself.
The Data Model is a flexible digital model made up of Objects and Relationships, for example:
The Data Model can include both Physical Equipment (e.g. a valve, pipe, vessel etc.) and Concepts (e.g. a Barrier Function, a System or Major Accident Hazard).
Each object can be contexualised by adding properties and relating it to any other object. In this way a full digital map of all the information about a facility is built.
The full context for a thing may be made up of relevant documents, facts about the thing, sensors that measure data on the thing, events, how it relates to other things and any abstract (i.e. conceptual) groups it is part of.
Accessing the Data Model
When the user accesses an object in the Data Model, the full context is immediately available; that is, all the properties and all the related information and objects. In Eigen Ingenuity the Common Menu is the always-available way of viewing this information.
The Common Menu gives a user instant access to contextualised information about an object in a Digital Twin. Items in blue are live links to other objects or data in other systems, e.g. documents.
The data model has the following key features:
- A graph not a hierarchy
- Flexible – continually grow and improve
- Links to source data – maintain trust and traceability
How is the Data Model built
The Data Model can be as small or as large as you like, for example it could just model the Production Wells on a facility to start with and then be expanded over time to cover more equipment.
The initial model is normally built from scripts and input files from existing systems/data[1] to identify all the objects and relationships.
Typically around 80% of the structure can be generated by scripts based on rules and regular expressions.
The last 20% often needs engineering input because either the relationships are not obvious or there are significant differences in naming conventions (or just plain errors). This is where Eigen’s extensive domain expertise makes a big difference.