DATA MODELING OF DIGITAL TWINS

The Azenzus Cloud based Dynamic Object Data Model of Things facilitates both “Digital Twins” and “Intelligent Apps”.

Azenzus is a dynamic cloud-based asset data management solution based on the Aspect Object principle.

The tool enables collaboration between disciplines and business processes across the enterprise.

There are four core data model aspects:

  • Function ( )
  • Location ( )
  • Product ( – )
  • Document ( )

Each aspect is modeled separately and enables you to create independent data models that are integrated into an overall data model. 

Data model aspects

Azenzus enables you to model you information from an early stage and refine the models as the project evolves.

3-layered data model

Azenzus is based on a data model developed by Covizmo where data is separated into three distinct layers:

  • Metadata (data definition)
  • Master Data (cataloging)
  • Instance Data (serial data)

Azenzus enables you to structure, catalog and classify information according to a method developed by leading experts and well described in international standards.

Azenzus is using Elasticsearch – very powerful search and analytics engine. The Kibana tool gives the data scientist an advance analysis and visualization tool for the Azenzus data model.

Turbo Charge Your CMMS

The purpose of Azenzus is to Turbo Charge existing computerized Maintenance Management Systems (CMMS).

By using a 3-layered data model it is possible to:

  • Classify complex equipment and documents
  • Catalog/standardize equipment and document master data
  • Register equipment and document instances
  • Create equipment and document viewing structures also called aspects.

The primary objective of the 3-layered object-oriented data modeling approach is to implement a data model used for all Covizmo services and products that can classify, catalog, structure, and register information used for Enterprise Asset Management (EAM) systems.

By using this structured data modeling approach, Azenzus makes it possible to create the foundation that is required for successfully implementing:

  • Reliability Centered Maintenance (RCM)
  • Failure mode Effect and Criticality Analysis (FMECA)
  • Reliability, Availability and Maintainability Analysis (RAM)
  • Safety Barrier Management
  • Materials Management (MM)
  • Document Management (DM)
  • Deep Learning Algorithms