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  2. Hello, i do analytics, based on data from AF Connector and always the end of the trend is dashed-line draw. I found out, that the last sample is actually considered "uncertain". Because of that, the capsule before the last (current) one is not closed, even when it should be. In the General Troubleshooting knowledge base, I found as following: https://seeq.atlassian.net/wiki/spaces/KB/pages/115185486/General+Troubleshooting+of+Connectors Unfortunatelly, I can not find this setting myself. I would like to switch uncertainity margin completely off, because I am sure, no source data can be changed after is collected by my source archive. Appreciate any help. Thank you.
  3. Last week
  4. Background As a starting point, I have a signal that indicates the process error code (Error) and 2 signals that indicate the current container (Container 1 and Container 2). I would like to create a histogram that summarizes which containers have the most frequent errors. More specifically, I want to know: For the Container 1 signal, what is the distribution of container values when the error code is equal to 44 and 47 For the Container 2 signal, what is the distribution of the container values when the error code is equal to 45 I want the results summarized as a single histogram. The following steps describe how this can be achieved using conditions and capsule properties. Solution 1. Create a condition with a capsule for each value change in the Error signal. This can be accomplished in Formula using the following syntax $errorSignal.toCondition() Note: the .toCondition() operator assigns a Value property to each capsule that indicates the value of the Error signal during the capsule. This property can be used for aggregation in a Histogram. 2. Filter the condition created in Step 1 to only include capsules with errors of interest for the Container 1 signal. This can be accomplished in Formula, using the following syntax: //Create intermediate conditions for each error $error1=$errorCond.keep('value',isEqualTo('44')) $error2=$errorCond.keep('value',isEqualTo('47’)) //Combine the 2 intermediate conditions $error1.combineWith($error2) 3. Assign a ‘Container’ capsule property to each of the capsules in the Error Cond 1 condition that indicates the value of the Container 1 signal. This can be accomplished within Formula, using the following syntax: $errorCond1.removeLongerThan(1week).transform($capsule -> $capsule.setProperty('can', $container1.average($capsule))) 4. Repeat Steps 2&3 for Container 2 a. Filter the condition created in Step 1 to only include capsules with errors of interest for Container 2. This can be accomplished in Formula, using the following syntax: $errorCond.keep('value',isEqualTo('45')) b. Assign a ‘container’ capsule property to each of the capsules in the Error Cond 2 condition that indicates the value of the Container 2 signal. This can be accomplished within Formula, using the following syntax: $errorCond2.removeLongerThan(1week).transform($capsule -> $capsule.setProperty('container', $container2.average($capsule))) 5. Combine the error conditions with container property to create a single, composite condition. This can be performed in the Composite Condition tool. 6. Finally, create the histogram based upon this composite condition.
  5. Hi, I have a pure cosmetic request to help build cleaner dashboards in an Org Topic. Can we have the option to change a cell border colour or turn off a cell border? The cell border just adds too much fluff to the dashboard. In the example below, you can see some cells borders around the white cells that I cannot remove. Thanks, Darren
  6. In the process industries, manufacturing requirements for an individual company can vary significantly over time due to lengthy research and development timelines and differences in market demand compared to forecasts. In pharmaceuticals, for example, companies may not have the capital or desire to invest in and build a manufacturing plant for their products as their expertise lies in research and development. Whether a smaller biotech or a large-scale producer, they must also contend with patent expirations on their most profitable drugs. These uncertainties for both big and small pharma have led to a significant increase in outsourcing of clinical and commercial manufacturing to contract manufacturing organizations or CMOs. While the pharmaceutical industry has seen a dramatic increase of projects being outsourced in recent years, contract manufacturing is also prevalent in many other industries including food and beverage, semiconductors, and upstream oil and gas. View the full article
  7. In the process industries, manufacturing requirements for an individual company can vary significantly over time due to lengthy research and development timelines and differences in market demand compared to forecasts. In pharmaceuticals, for example, companies may not have the capital or desire to invest in and build a manufacturing plant for their products as their expertise lies in research and development. Whether a smaller biotech or a large-scale producer, they must also contend with patent expirations on their most profitable drugs. These uncertainties for both big and small pharma have led to a significant increase in outsourcing of clinical and commercial manufacturing to contract manufacturing organizations or CMOs. While the pharmaceutical industry has seen a dramatic increase of projects being outsourced in recent years, contract manufacturing is also prevalent in many other industries including food and beverage, semiconductors, and upstream oil and gas. View the full article
  8. Thank you for that clarification, Darren. I have included these details in a Support Ticket. We appreciate your feedback! Regards, Katie
  9. Hello Katie, Thanks for the interest! The multiple output signals are needed for a multivariate estimation technique to compare estimated (or expected) signal values with vs. actual values. The prediction tool is used to calculate the estimated or expected signal value. I then create conditions on the absolute deltas between he estimated outputs and their actuals to provide early warning anomaly detection of deviations away from expected values. At the moment I need to build a seperate predictions to obtain the estimated signal for each output... I have attached a pdf with some quick sketches and an example to help illustrate why this is needed to speed up anomaly detection config. Thanks, Darren MET exmple.pdf
  10. Hi Darren, Can you give me a little more information about what you are trying to accomplish with multiple outputs? Given one set of selected inputs, are you hoping to create a prediction output for each scale (linear, logarithmic, polynomial, expanded basis) to compare against each other? Thank you, Katie
  11. Thank you for your input, Darren. I have logged your advocacy for this feature request in a Support Ticket. You will be notified through that ticket about development updates. Regards, Katie
  12. Hi Theresa, I like this feature, a way to set some global defaults would also help to introduce some standardisation and would save configuration time... e.g. setting the default labels for all charts to show the UOM on the y-axis. Regards, Darren
  13. While building an asset tree using spy.assets, the display items of a worksheet can be defined under @Asset.Display(). The list below shows the options that can be set for each parameter of the display pane: Color: str = any valid color hex for example #4055a3, #068c45, #9d248f. Line Style: str = {'Solid', 'Short Dash', 'Short Dash-Dot', 'Short Dash-Dot-Dot', 'Dot', 'Long Dash', 'Dash-Dot', 'Long Dash-Dot', 'Long Dash-Dot-Dot'} Line Width: float = {1, 1.5, 2, 2.5, ...9.5, 10} Lane: int = {1, 2, ...} Samples Display: str = {'Line', 'Line and Sample', 'Samples', 'Bars'} Axis Auto Scale: bool Axis Align: str = {'Left', 'Right'} Axis Group: str = {'A', 'B', ...} Axis Max: float Axis Min: float One example of display items set using @Asset.Display(): @Asset.Display() def Bar_Graph (self, metadata, analysis): worksheet = analysis.worksheet('BarGraph') workstep = worksheet.workstep('BarGraph') workstep.display_items = [{ "Item": self.Signal_1(), "Axis Group": "A", "Axis Auto Scale": True, "Lane": 1, "Line Style": "Solid", "Line Width": 10, "Samples Display": "Bars", "Color": "#4055A3" }, { "Item": self.self.Signal_2(), "Axis Group": "B", "Axis Auto Scale": True, "Lane": 1, "Line Style": "Short Dash", "Line Width": 1, "Samples Display": "Line", "Color": "#9D248F" }, { "Item": self.self.Signal_3(), "Axis Group": "B", "Axis Auto Scale": True, "Lane": 1, "Line Style": "Solid", "Line Width": 1, "Samples Display": "Line and Sample", "Color": "#CE561B" }, { "Item": self.self.Signal_4(), "Axis Group": "C", "Axis Auto Scale": False, "Axis Align": "Right", "Axis Max": 100.5, "Axis Min": 10, "Lane": 1, "Line Style": "Solid", "Line Width": 1, "Samples Display": "Samples", "Color": "#00A2DD" }] workstep.display_range = {'Start': '2020-06-11T00:00:00', 'End': '2020-07-12T00:00:00'} workstep.view = 'Trend' return workstep
  14. Hi @Devin, When you open the import from CSV file tool, select import file as condition. If you scroll down to the "+" icon that says "Optional Settings" you'll see that the default treatment of CSVs imported as a condition is to treat all columns as capsule properties.
  15. Hi @Allison Buenemann. Thanks for the reply. Could you further expound (screenshots appreciated)? I read the wiki page above but it doesn't really show how to import the capsule properties. It just infers you can. Maybe I missed it.
  16. Hi @Devin, beginning in version R22.0.48 this got much easier with the CSV Import Tool 2.0. You can learn more about the CSV Import 2.0 tool from this https://seeq.atlassian.net/wiki/spaces/KB/pages/537690127/Import+CSV+Files+2.0. If you need assistance upgrading your software to version 48+ feel free to reach out to your account manager or sales executive.
  17. Hi @Allison Buenemann. I'm so glad I ran into this post!! This is exactly what I need to do. I did notice this post is over a year old, and wondering if there is now a easier\less formula intensive way to do this? It's so common to have additional attributes in spreadsheet data that need to be in SEEQ as capsule properties I'm hoping the process is perhaps more automated, "spoon fed", faster, streamlined now, etc. Thanks again.
  18. Sometimes it is desired to have custom units of measure display in Seeq Scorecards. This could be used when the signal or condition has no units or when you want to add a custom display or a unit that might not be a recognized Seeq unit. You can use Seeq's Number Format customization in the item properties panel to add custom text units to your scorecard. Here are some examples showing different ways to add text display units. The key here is including the text in quotation marks. More information on how to customize these number displays, including the syntax for adding custom text, can be found by clicking the "?" icon next to "Number Format".
  19. Please can the default labels be set to show the UOM on the y-Axis, it is a little frustrating to set that every time and it is good engineering practise to always show the UOM on the axis.
  20. When building predictions, it would save a lot of time if there was an option to select multiple outputs for the set of selected inputs. Each new predicted signal will need a name field to define the output signal name. At the moment, I have to configure a seperate prediction for each output signal.
  21. Earlier
  22. An optional workaround to having the values show directly on top of the histogram bars is to combine histogram and scorecard views in an Organizer Topic. Here is an example of doing this:
  23. Hi Jaswin Thanks for reaching out! Unfortunately this is not currently offered in Seeq. I did file a feature request with your email address and company info and you will be notified if this feature is added into the Seeq product. Please let us know if we can help you in any other way.
  24. I would like to have the value to show directly on top of my histogram, doesn't seem to be able to do so with the current function. Any advice?
  25. The workaround discussed in this forum post is another way to visualize multiple series together on one scatter plot, and holds up so long as the variables can be displayed on the same y-axis scale. For dramatically different y-axis scales, Seeq Data Lab can be used to produce scatter plots with multiple y-axes.
  26. Hi Mattheus, You can do this by using the move (v49+) or delay (<=v48) function. For example, your equation would be: ($signal.move(5s)+$signal.move(10s)+$signal.move(60s))/3
  27. Hello, Is there any function or manner to get the value of a signal in the past? For example, let's us suppose that I have a signal A, and I would like to make the following calculation: Calculation = (A( * - 5s) + A(* - 10s) + A(* - 60s))/3 Where A(*-t) would get the value of A at 5 seconds ago, it could be interpolated value or the nearest available value. Any help? Regards, Mattheus
  28. Hi Mike, by default the size of the tiles reflects the number of assets under the specific asset. In this example, as Cooling Tower 1 has more assets belonging it then Cooling Tower 2, the area of the rectange is bigger: Assets below Cooling Tower 1: Assets below Cooling Tower 2: As you may notice the shape of the rectangles for Area J and K in Cooling Tower 1 is different from the other rectangles, although the size is the same. Resizing the browser circumvents this issue and displays the rectangles all in the same shape: You can override the size of each item individually as described here: Hope this helps. Regards, Thorsten
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