Functional Tips & Tricks

Did you know you could add certain content from outside of TrendMiner to your dashboards? The external content tile allows you to add additional information to your dashboards that doesn’t necessary originate from your process data. Many often include training videos, images, and Visio block flow diagrams, stored on SharePoint pages, to give better context to those interpreting dashboards shared across teams or shown on control room displays.​@EdwardB recently shared some interesting sources that allow embedding weather related widgets to DashHub. For this, you can try these twosources: https://widget.airnow.gov/ and https://embed.windy.com/Do you have other interesting applications you’d like to share with the community? Comment below! 

In this article we'll dive into a worklow to create a multivariate parallel coordinates plot that can be filtered by time and calculations. In this specific image, we're looking at the hourly averages of measurements (Power, in and outgoing: flow, temperature, pressure) of a Sales Gas Compressor unit Workflow 1. Import time-tags as DISCRETE (I'm attaching the .csv file for Europe - Brussels, let us know if you need another timezone in the comments!). This action only needs to be done once. Once imported, the tags will be available for all users. 2. Pick the desired Context period on the bottom of the focus chart in TrendHub 3. Add the relevant tags to your process and the imported [t]HOUR, [t]DAY, [t]MONTH and [t]YEAR tags from step 1. 4. Do a Value based search to look for the condition when the hour-tag was constant: 5. Add Calculations that relate to the process you'd like to understand better. Typically, having the average of all other relevant tags should be a good starting point

 BackgroundTrendMiner provides a set of Time/Date Tags by default with installation. These tags deliver time and date information directly from the system – independent of any process data – and are available for all time zones: TM_hour_* – Hour of the day TM_day-* – Day of the month TM_month_* – Month TM_year_* – Year Time/Date Tags in TrendMinerTime/Date Tags for all time zones in TrendMinerThey allow for precise configuration of searches, calculations, or monitors tied to specific moments or recurring time patterns – think daily reports at a fixed time or tracking values at the beginning of each month.For full details, see the User Guide. 🎓 Deep Dive & Training ResourceWant to go further? Check out these advanced trainings for practical, hands-on examples: Mastering Tag Types in TrendMiner – Tips, Tricks & Hands-On Exercises (Exercise 3) Event Analytics in Action: Gain Deeper Process Insights (Exercise 2)  🌟 Community Inspiration – Related PostsHere are great examp

❓What Are Custom Calculations?Custom Calculations in TrendMiner empower advanced users to define new tags using Python scripts, enabling analytics and data transformations beyond what’s available through standard formulas or aggregations. This feature is powerful for creating custom KPIs or logic that’s specific to your plant or workflow. 🗂️ Repo Structure OverviewThe TrendMinerCS/custom-calculations repo is your go-to resource for getting started with Custom Calculations. It includes: A Jupyter notebook with a detailed explanation of the workings of custom calculations and the TrendMiner sdk. A detailed README outlining the possibilities with examples and screenshot. Example Python scripts for common calculation scenarios. Templates to help you quickly build your own scripts. Clearly organized folders so you can browse by use-case or script type. Browsing this repo is the fastest way to kickstart your own Custom Calculations and learn best practices directly from TrendMiner a

Have you ever had a situation were you would like to see how your measurement is doing and how close is it of its allowed Upper and Lower limits?  Have you ever tried to create a dashboard where you can easily see the status of your equipment and in which zone is it performing?Up until now, in TrendMiner we could create a monitor that tells/notify us whenever a limit is surpassed or reached. Additionally, in a dashboard we could create a monitor tile that will change when this monitor has been triggered. But this only allows 2 status: On/Off, Good/Bad, etc. If we want to have more statuses, we were already limited by the use of only one tile. Monitor tile configured with 2 states. An easy workaround is usually to create a traffic light system, where monitor tiles are used for each different status. For example, in a tank level, in order to have Low, Intermediate and High level, we would need 3 monitor tiles as shown in the picture. Traffic light system with 3 states for a tank level. H

 Background:In many use cases, it’s not just the type of event that matters — its duration can be just as important. While TrendMiner allows you to define a minimum duration when performing a search, sometimes you want to look only for events that fall within a specific time window, for example between 2 and 5 hours.Here's how to do that using two simple approaches. ✅ Option A: Refine Search Results by Duration RangeUse this approach to narrow down results after you’ve run your main search.Steps: Run your event search based on the relevant value or digital criteria. In the search panel, click "Event Analytics". Set the minimum duration to 2 hours and the maximum duration to 5 hours. Your results list will now only show events that occurred within this defined time frame. 🔍 Tip: Perfect for quickly filtering without modifying your original search setup. Search for events with a duration of 2 hours to 5 hours 🚫 Option B: Exclude Longer Events Using a Static FilterThis method help

In TrendMiner, time tags play a crucial role in process analysis. They allow users to define and segment data based on specific hours, days, weeks, months, quarters, and years, enabling precise time-based calculations. Many key performance indicators (KPIs) rely on time-based reporting, such as: Daily production totals Hourly average flowrates Monthly energy usage Quarterly business metrics Example of HOUR time tags in TrendMiner.​​​​TrendMiner time tags for the US Central time zone.Why Time Tags Matter in TrendMinerTime tags can be especially useful when defining formula tags that incorporate a time-based component. For example, you might need to calculate averages over specific time intervals or align production metrics with financial reporting periods. Like any other tag, time tags can also be utilized in value-based searches and monitors.Handling Less Common Time ZonesTrendMiner includes predefined time tags for commonly used time zones, making it easy to apply time-based ana

I just saw a question pop up in the community asking whether TrendMiner has built-in steam equations. While they are not built-in, here’s a way to start using steam equations in TrendMiner...A while back, I implemented the numeric steam table equations found on https://iapws.org/relguide/IF97-Rev.html into TrendMiner Formula Tags. I am posting those here in the hopes it can help some other users too.The attached zip file contains txt files for formulas that can be copy-pasted into a Tag Builder formula for steam table calculations.Formula units are currently in Celsius and bar, so you might need to adjust accordingly. Text search and replace should work to change the input units, for example 'P' -> '(P*1000)' to use tags that are in mbar. To change the output unit you can simply multiply the formula by a constant value.

 IntroductionDaily production is a key performance indicator (KPI) in continuous processes, helping process experts track efficiency and performance. However, in many cases, daily production is not readily available as a default variable in data historians. A recent question in the TrendMiner Community addressed this challenge: How to calculate a daily average of a signal with a single result per day?. This article explains four different approaches to calculating daily production in TrendMiner, depending on the user’s needs. 1️⃣ Continuous Rolling Last 24 Hours Production 📌 BackgroundThis method ensures that at any given time, the production of the last 24 hours is always available as a continuously updating value. This is particularly useful for real-time monitoring and trend analysis.🛠 Steps Load the relevant tag related to production. Set the context and focus chart to visualize the required time range. Create a new aggregation: Select the production signal. Use a back

Applying Transformations to Your Tag Data in TrendHub In process data analysis, relationships between variables are often assumed to be linear. However, real-world process relationships can be more complex and often are. For example, the relationship between pressure drop and flowrate is only linear under laminar flow conditions. In turbulent flow, which is more common in industrial processes, the relationship follows a quadratic function, as described by the Darcy-Weisbach equation.Because of these complexities, it is crucial to apply transformations to your data to properly analyze and interpret process relationships. TrendMiner's formula tag builder provides a way to achieve this.Example: Analyzing Pressure Drop Across a Flow PumpIn this example, we analyze the pressure drop across a pump using two tags: Flowmeter Tag (Q) - “TM-HEX-FI0620” Pressure Drop Tag (ΔP) - “TM-HEX-PDI0620” When plotting these tags on a scatterplot, we observe that the relationship is not linear. Instead, i

Using TrendMiner’s Cross-Correlations Tool for Root Cause Analysis One of the most powerful features within TrendMiner is the cross-correlations tool. It is especially useful when conducting root cause analysis because it helps identify correlated tags that could serve as early indicators for your tag of interest. Identifying the Root Cause of a Process Disturbance Let’s look at an example of how to identify the root cause of a process disturbance.A process engineer monitoring a reactor unit notices an abnormal temperature spike in the reactor. The unit supervisor asks the engineer to determine what may have caused this increase. However, without immediate input from board operators and field operators, it can be difficult to know where to start. Reactor temperature fluctuations can result from many different factors, making troubleshooting a complex task.This is where TrendMiner can help.By using the cross-correlations tool, TrendMiner can quickly compute correlations between the reac

 Hello 🖐🏻Identifying periods where parameter readings increase or decrease is crucial for process monitoring!🤔Why it matters? Changes often indicate potential issues or opportunities for optimization.✍How to analyze? Calculating the derivative of a tag allows for a more precise assessment of how sensitive a process is to fluctuations in specific parameters.📊 In TrendMiner : Different methods are available to determine the derivative based on the type of analysis needed. 👉🏻 Preparation: Smoothing Signals For noisy or highly fluctuating signals, it is recommended to perform an aggregation before calculating the derivative.This helps achieve a more accurate approximation of the derivative of the selected function.Recommended Aggregation:Tag: The tag for which the derivative should be calculated Operator: Average Direction: e.g., Backward Aggregation interval: e.g., 10 minutes   👉🏻 Option A: Calculating the Derivative Using a Formula The derivative can be determined by calculating

Best Practice for Tag Nomenclature in TrendMinerOrganizing tags effectively is crucial for efficient data analysis in TrendMiner. A clear and consistent naming convention allows teams to quickly identify, manage, and collaborate on tags. To address this, we recommend adopting a structured format that simplifies tag creation and ensures long-term usability.Using a standardized approach benefits everyone involved. Whether you’re searching for specific types of tags, identifying a calculation, or finding the creator of a custom tag, a proper naming convention saves time and effort. This system ensures that tags are intuitive and easy to understand, even for new team members, while also enabling existing users to locate information quickly and reliably. Introducing a Drop-Down Menu Solution in ExcelTo make this system even easier to use, we’ve developed an Excel template where users can generate tags effortlessly. The template features drop-down menus for each part of the tag name, so user