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  1. Summary: Many of our users monitor process variables on some periodic frequency and are interested in a quick visual way of noting when a process variable is outside some limits. Perhaps you have multiple tiers of limits indicating violations of operating envelopes or violations of operating limits, and are interested in creating a visualization like that shown below. Solution: Method 1: Boundaries Tool One method to do this involves using the boundaries tool. This tool is discussed in Step 3 of this seeq.org post, and results in a graphic like that shown below. Some frequently asked questions around the above method are: Is there a way to make the different levels of boundaries different colors? Is there a way to color the section outside of the limits rather than inside of the limits? Method 2: Scorecard Metrics in Trend View Step 1. Load the signal you are interested in monitoring as well as the limits into the display pane. The limits can be added directly from the historian, or if they do not exist in the historian they can be created using Seeq Formula. Step 2. Open a new Scorecard Metric from the tools panel, create a simple scorecard metric on your signal of interest, with no statistic. Click the "+" icon to optionally enter thresholds, and add the threshold color limits that you are interested in visualizing. Note that the thresholds input in the boundary tool can be constant (entering a numeric value) or variable, selecting a signal or scalar.
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  2. Thanks for the post, Allison! I wanted to share how I took what you did and made it into rolling a "year to date" (YTD) metric, and other comparable metrics. I work in hydroelectric generation, so my utility operates a few dams. One of the things we want to track is how close our upstream water level (headwater) gets to our buffered operating limits (in this case I'm looking at buffered lower limit dips). Here's a screenshot of the example scorecard metrics I created: And here are the dependency trees: Here's how I did it: So, starting from the deepest part of the trees: ‘Yearly 1’ is common to all three. It is standard Periodic Condition for Yearly capsules. ‘Now Condition’ follows the forum post. Make this formula: condition(1min, capsule((now()-1min), now())) ‘Year Ago Now’ is based on the ‘Now Condition’ but you subtract off another year. Make this formula: condition(1min, capsule((now() - 1min - 1year), (now() - 1year))) ‘Current Year’ is a composite condition of ‘Yearly 1’ and ‘Now Condition’ using “Touches” ‘Last Year’ is a composite condition of ‘Yearly 1’ and ‘Year Ago Now’ using “Touches” ‘Rolling Year Condition’ is a formula. condition(1year, capsule((now()-1year), now())) ‘Year to Date’ is a composite condition of ‘Current Year’ and ‘Rolling Year Condition’ using “Intersection” (i.e. when is it both the current year and happening within the last year.) ‘Last Year to Date’ is a composite condition ‘Last Year’ and ‘Rolling Year Condition’ using “A minus B” (i.e. when is it last year but not within the last rolling year.) Then you can create your usual value based conditions. I used RI Headwater less than 610. Then you create your metrics! Here’s the screenshot of the Year to Date metric. To get Last YTD, you simply change the condition at the bottom to ‘Last Year to Date.’ The metrics refresh when you refresh the screen!
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  3. Overview This method will provide a simple visualization of externally determined control limits or help you accurately calculate new control limits for a signal. Using these limits we will also create a boundary and find excursions for how many times and for how long a signal deviates from the limits.These created signals can be used in follow-on analysis search for periods of abnormal system behavior. In this example we will be creating average, +3 Std Deviation and -3 Standard Deviation boundaries on a Temperature Signal. Setup Signals In the Data tab, select the following: Asset → Example → Cooling Tower 1 → Area A Signal → Temperature Option 1: Manually Define Simple Control Limits From the Tools tab, navigate to the Formula tool. The Formula can be used to easily plot simple scalar values. If you already have calculated values for the upper and lower limit just enter them in the formula editor with their units as shown in the screenshot below. Formula - Simple Upper Limit 103F Formula - Simple Lower Limit 70F Option 2: Calculate The Control Limits From the Tools tab, navigate to the Formula tool. In formula we are going to define the time period over which we want to calculate our control limits as well as the math behind those limits. Step 1 - Calculate the upper limit Variables Name Item Type $Series Temperature Signal Formula $calcPeriod = capsule("2018-01-01T00:00:00-06:00","2018-05-01T00:00:00-06:00") $tempAve = $Series.average($calcPeriod) $tempStdDev = $Series.standardDeviation($calcPeriod) $tempAve + 3*$tempStdDev Description of Code $calcPeriod → This is the time range over which we are going to calculate the average and standard deviation of our signal. The start and end time of our period must be written in ISO8601 format (Year - Month - Day "T" Hour : Minutes : Seconds . Fractional Seconds -/+ Timezone) $tempAve → Intermediate variable calculating the average of the temperature signal over our calculation period $tempStdDev → Intermediate variable calculating the standard deviation of the temperature signal over our calculation period $tempAve + 3*$tempStdDev → Example control limit calculation Step 2 - Duplicate your formula to calculate the lower limits Click the info icon in the details pane next to your calculated upper limit signal. From the info panel select duplicate to create a copy of the formula. With this copy simply edit the formula to calculate the lower limit. $calcPeriod = capsule("2018-01-01T00:00:00-06:00","2018-05-01T00:00:00-06:00") $tempAve = $Series.average($calcPeriod) $tempStdDev = $Series.standardDeviation($calcPeriod) $tempAve - 3*$tempStdDev **Alternate method number three -- if you wanted $calcperiod to actually changed based on the previous month or week of operation you could use signal from condition based off a periodic condition to achieve this solution. Step 3 - Visualize Limits as a Boundary Using the Scorecard Metric to connect the process variable and upper and lower limits. Select Temperature as your item to measure. Add threshold for your upper and lower limits. Default is to add a fixed value. By clicking on the scalar icon to the left of the green "x", you can select a signal as your threshold limit. You can change the colors of the different threshold or color only the area between the threshold as shown below. Once you click execute, you will see a new scorecard metric with the shaded area between the boundaries and the original signal. Step 4 - Create Capsules when Outside the Boundary Using the Value Search tool, create a condition for when the signal is outside the limit signals. Name your new condition, select temperature as the input signal, select <> not between, click on the scalar icon to select a signal as your limit, and use the upper and lower limit signals as your upper and lower limit, respectively. Step 5 - Create a Scorecard to Quantify How Often and How Long Boundary Excursions Occur Create a Scorecard to count how many and how long and what % of total time these excursions are occurring. Create each metric using the Scorecard Metric tool and the Count, Total Duration and Percent Duration statistics. Use a Condition Based scorecard to get weekly or monthly metrics. Step 6 - Plot how these KPIs are Changing Over Time By creating a signal which plots these KPIs over time we can quantify how our process variable is changing relative to these limits. To begin, determine how often you would like to calculate the KPI per Hour/Day/Week/Month and create a condition for those time segments using the Periodic Condition tool. In the screenshot below we are creating a weekly condition with capsules every week. Using the Signal from Condition Tool count the number of Outside Simple Boundary capsules which occur within each weekly capsule. This same methodology can be used to create signals for total duration and % duration just like in the scorecard section above. For each week the tool will create a single sample. The timestamp placement and interpolation method selections will determine how those samples are placed within the week and visualized on the chart. The scorecard metrics that you created above can also be trended over time by switching from Scorecard View to Trend View. Content Verified DEC2023
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