Jump to content

Technique for Scaling Data Exports across Assets


Recommended Posts

  • Seeq Team

Asset groups and asset trees (link) are used frequently in Seeq for asset swapping calculations, building treemap visualizations, and scaling tabular results across assets. In some cases, users want to export calculated results for assets from Seeq Workbench to Excel or perhaps to Power BI. The following example illustrates a technique for doing this efficiently with a single export. 

1. Asset group for 8 furnaces contains an "Outlet Temperature" signal that we want to calculate and export daily statistics (avg, std deviation, min, max) for:

image.png

2. Note that the "Daily Statistics" condition is created with a Formula that is part of the asset group. This is key to enabling the data export across all assets. See the formula for the "Daily Statistics" condition below for Furnace 1. Note that we create a daily condition and then add the temperature statistics as capsule properties, and assign an asset name property. These details are also essential in setting up an efficient export. As a reminder, we need to edit the "Daily Statistics" formula for each furnace to assign the correct furnace number to the Asset Name capsule property. For this example (only 8 assets), this is easy to do manually. For a large asset group (50, 100 or more), a better approach would be to create an asset tree using Data Lab, and programmatically create the individualized "Daily Statistics" conditions. 

 

image.png

 

3. Next, we navigate the asset group and add the Daily Statistics condition for each furnace to the trend display in Workbench, which makes it easy to set up the "Daily Furnace Statistics for Export" in step 4.

 image.png

 

4. Create the "Daily Furnace Statistics for Export" condition which will have overlapping daily capsules for the 8 furnaces. Here, we combine the separate Daily Statistics conditions (for all 8 furnaces) into a single condition. For the export to work as expected in a later step, we need to slightly offset the capsules using the move() function, so that they do not have identical start times. 

image.png

 

5. Next, we visually check the capsules and their properties on the trend (Asset Name and Daily Avg) and in the capsules pane on the lower right. Everything looks as expected, we have a capsule for each furnace for the day of May 24.

image.png 

6. The export to Excel or to other applications via OData can now be set up. The key is to export only the "Daily Furnace Statistics for Export" condition, and to set the time range appropriately based on your objectives. Here, we only want the results for 1 day:

image.png

7. Checking the export on the Excel side, all looks good. We have the daily statistics, scaled across all furnace assets, with one row for each furnace:

image.png

 

To summarize, the following are keys to this technique for exporting calculation results across all assets, from Seeq Workbench:

Store the calculation results as capsule properties in a condition that is an item in the asset group, and also assign an asset name property (see Step 2 above). In this example we used a daily time basis for calculations, but the techniques can be applied and extended for many scenarios. 

To store the results across all assets, create a single condition for export, which is a combination of all the individual asset "calculation results" conditions, and offset capsules slightly as needed to avoid capsules having identical start times (see Steps 3 and 4 above). 

In this example, we only had 8 assets so all formulas could be created interactively by the user. For large asset structures, the asset tree and formulas, including the final condition for export, can be created programmatically using Data Lab (link).  

Edited by John Cox
formatting changes
Link to comment
Share on other sites

  • 8 months later...

Hi John - thank you for the expansive detailing on this solution.  Do you know if any updates have been made in R61-R64 that would better support large asset trees? We have about 500 instruments and 10 calculated signals from a PI Asset Framework hierarchy that we would like to expose to Power BI. Is your technique above still the only way to scale it across the entire tree?

Thanks, David

Link to comment
Share on other sites

  • Seeq Team

Hi David, 

There have been significant OData export enhancements in the R62-R64 versions of Seeq, related to performance, export options, managing exports, etc. (more here at the What's New link). 

If you are wanting to do a single OData Export to Power BI across all assets, the approach outlined above may still be your best option (and note that the formulas can be created programmatically using Data Lab).

Before going down that path though, I would strongly recommend you sign up for an upcoming Office Hours slot and discuss the export use case details with a Seeq Analytics Engineer - there may be other options to consider. 

Link to comment
Share on other sites

Create an account or sign in to comment

You need to be a member in order to leave a comment

Create an account

Sign up for a new account in our community. It's easy!

Register a new account

Sign in

Already have an account? Sign in here.

Sign In Now
×
×
  • Create New...