Creating Live Models
In some cases, customers have existing models that describe how their system works - but they are usually offline models that are done by hand or in spreadsheets.
With the rise of Machine-Learning, they may also have predictive, simulation or analytic models that can be used to improve how people operate equipment.
If you want to make these models 'live' - or if you want to perform any other comparisons, calculations and modelling using your live process data - you can use ModelHost.
Why Modelhost?
ModelHost has a some key benefits…
* Connects multiple different models using a single connection, reducing your need for ARDI user licenses,
* Allows individual models to share information so you can chain independent models together and perform meta-analytics,
* Allows easy goal-seeking and other complex analysis, which allows you to use your existing models in new ways and to answer questions that they weren't specifically designed to answer.
* The Modular Output System allows you to export any new metrics - such as simulated values, KPIs, totals etc - to other systems or back into ARDI.
* Output data is automatically provided via OPC-UA, allowing it to be easily integrated into industrial systems.
Example Models
Two models are included in the examples.
The math-based model does some simple math calculations. The first is a calculation to predict failure probability for a singe turbine, the second uses a dynamic query to build a model output for each asset of a given type.
The ml-based model uses a machine-learning model to simulate the behaviour of a subsystem.
Accessing Example Model Data
Model values are available via the OPC-UA protocol.
We suggest a free UA-browser tool such as UAExpert - follow these instructions to see the data coming from the model.