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Found 3 results

1. ## Calculating Cycle Run Length and Comparing Equipment Cycles

I have a piece of equipment that regularly goes through cycles and I want to compare the cycles. In this case I know the exact date and time of the equipment runs so I have used the Custom Condition tool to specify my Previous Run and Current Run. Custom Condition allows you to enter dates for the condition you are interested in. This can also be done in formula. To create the condition for my Next Run I used Seeq's formula because this run is currently on going and I do not know the end date. This approach allows me to specify that this condition end at now. condition(2d, capsule('2020-06-01T17:48Z', now())) Now that I have defined my Previous, Current and Next runs I want to calculate the run time of each of those periods. I can do this in Seeq's formula tool using the time since function. This will allow me to create a signal whose value is the time since the start time of a condition. This signal will end at the end of the condition. In this case my time counter will be in hours, if you wanted it in days instead you would change the 1h to 1d. timeSince(\$condition, 1h) I duplicated this formula three times for my previous, current and next runs. Remember, you can always duplicate a formula by clicking the "i" by item properties. You can compare the run lengths of the 3 runs by putting them on the same lane and same axis. You'll noticed my Next Run has just started so the time since for it is much smaller. Lastly, you can switch to capsule time view to compare the run length as well as different signals over the run. In this case we are looking at the temperature of each run as well as the run length. You could imagine using this approach to monitor heat transfer coefficients, reactor temperature, reactor conversion, or % sulfur removed.
2. ## Mean Kinetic Temperature (MKT) Calculation

In many industries (pharmaceuticals, food and beverage, etc.), mean kinetic temperature (MKT) is used to measure the temperature fluctuations of a material during storage and shipment. Mean Kinetic Temperature is a non-linear weighted average temperature that is set up to provide an impact on product stability. In general, product stability follows an exponential trend with temperature as it is inherently a decomposition reaction of the desired product. Therefore, the mean kinetic temperature takes into account the exponential reaction rate to determine the average temperature weighted by the kinetics of the reaction over time. The formula for mean kinetic temperature is: Where: is the mean kinetic temperature in Kelvin is the activation energy (in kJ mol−1) is the gas constant (in J mol−1 K−1) to are the temperatures at each of the sample points in kelvins to are time intervals at each of the sample points This formula can be inserted into Seeq through a couple of steps: 1. Calculate the time intervals for each of the data points (tn). In many cases these are evenly spaced and the formula simplifies, but in case they are not, this can be calculated in Seeq Formula by creating capsules for each data point and then aggregating the duration of those capsules: \$temp.tocapsules().aggregate(totalduration(),\$temp.tocapsules(),startkey()).tostep() 2. Calculate the exponential relationship for each sample point (t*exp(-deltaH/RTn)) using Seeq Formula. For this example, delta H was set to 83.14 kJ/mol: \$H = 83.14kJ/mol \$TimeInterval*CONSTANT.E^(-\$H/CONSTANT.R/\$temp) 3. At this point, the desired time period to perform the MKT calculation over must be selected. This can be done by creating a capsule with the Custom Condition tool. The desired time period can be as long or short as desired. 4. The next step is to sum the numerator and denominator of the natural log portion of the MKT calculation. These summations across the time period signified in step 3 can be performed with the Signal from Condition tool by selecting the sum statistic, the time period from step 3, and the aggregation at the middle timestamp of the condition. This step should be performed for both calculated signals from steps 1 (time intervals for denominator) and 2 (exponential rates for numerator). 5. Finally, the MKT calculation can be calculated with Seeq Formula: \$H = 83.14kJ/mol ((\$H/CONSTANT.R)/(-ln(\$TotalizedNumerator/\$TotalizedDenominator))) .convertUnits('K') As an example, below is a graph showing this calculation being done over multiple time periods of interest (green capsules at top):
3. ## Creating a varying time scale

Is Seeq able to create the graph below? Note that the left-hand side plots the yearly average, while the right-hand side plots the monthly average. Ideally I would like this all displayed on one graph. Currently, our only workaround is to create 2 separate graphs (one for the yearly averages and one for the monthly averages) and display them side by side.
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