Background

Often times, we find ourselves wanting to know when a certain tag changes state. For example, if we have a batch process, I’d like to know when I transition from one phase to another in the process. Or for a multi-product line, I would like to know when we switch from manufacturing product A to product B. Not only would we like to know when these state changes occur, but also it would be useful to analyze the data per state or segment. Consider the batch process example again - it would be nice to know the duration of each phase. Or even, what is the maximum temperature at each phase of the batch process?

In TrendMiner, we can quickly answer these questions by conducting a constant Value Based Search (VBS). When selecting constant in a VBS, we ask TrendMiner to identify every change of state or level. I say level too because constant VBS can apply to analog tags in addition to string and discrete tags. Below I will detail the steps to create a constant VBS.

Step 1 - Create the VBS

To initiate a constant VBS, navigate to Search on the left-hand side toolbar and select create new VBS.

Step 2 - Select the desired tag, choose ‘Constant’ for the condition, and specify the minimum duration

Step 3 - Execute the search

Confirm that the time period for the search is satisfactory. If not, adjust the context bar time period. The context bar time period sets the VBS search period.

Step 4 - Verify search results

Confirm that the search results are what you’d expect.

Step 5 - Data analysis

From here, we have multiple options. The below list shows how we can proceed with our data analysis:

• Filter the search results by duration
• Export the search results to excel
• Save the search and enable a monitor with this search
• Add calculations onto the search (up to 30 calculations can be added to the VBS)
  • For example, I can find the max pressure for each product run
  • Once the calculation has been created, I can sort the search results by the calculation (sort ascending or descending by max pressure)

I hope this functional tip/trick helps with your data analysis in TrendMiner. Please comment below your use cases or if you have any questions!