Asset Model Concept

This chapter provides an example on how to implement the Asset Model concept leveraging the AVEVA Insight Data Adapter. These implementation strategies and rules can be extended to the on-premises data sources (Historian, MES, and so on).

The following objectives should be considered while creating an asset model:

• BI Gateway operates as an abstraction layer by processing the dimensional model regardless of the distinct assets and FQN/Tagnames to consider.

• BI Gateway needs to resolve

  • “what to do” (e.g. populate a dimension, compute a measure calculation, execute backfill processing, run a scheduled refreshed, etc.) from the dimensional model and its internal mechanism (custom queries, scheduler, etc.).

  • “How to do” (e.g. which FQN to consider for populating batch dimension, which retrieval mode to consider, does it require dataset manipulation, which asset and asset’s behavior to consider, etc.) from the asset model capability of AVEVA Insight.

Asset model structure

Asset model concept can be configured using the BI Gateway Insight Data Adapter for:

• Managed Historian – Tagname Dictionary (built-in and Tag extended properties)

• MES - Equipment Efficiency Model

• CIM – Common Intelligent Model

It can be combined in such a way as:

1. Basic asset model

   • Managed Historian only

2. Intermediate asset model

   • Managed Historian

   • MES Efficiency

3. Advanced asset model (Future Release)

   • Common Intelligent Model

REST APIs

AVEVA Insight contents is mainly exposed through REST APIs which allow interacting with the solution such as:

• Historian Data REST API (Managed Historian API)

• Equipment Efficiency REST API (MES API)

• Common Intelligent Model REST API (CIM API)

For more information about available API endpoints, see Using Custom Queries to Create Custom Source Data Items.

Each of the above APIs allow upload or retrieval requests using a web browser or a client-side applications such as:

• Microsoft Excel (2013, 2016, or Office 365)

• Business Intelligence (BI) systems

  • Tableau

  • Microsoft Power BI

• Postman