Functional Tips & Tricks

 In industrial data analysis, precisely examining short events is crucial for optimizing processes and preventing disturbances. Short events, which are shorter than the index resolution, present a unique challenge as they can easily be overlooked. Here, I will show you how short events can still be analyzed in TrendMiner using a value-based search.Examples of short eventsExamples of short events include sudden pressure spikes in pipeline systems, which may indicate valve malfunctions or blockages, temporary temperature fluctuations in reactors, which can point to unexpected chemical reactions, and brief electrical spikes in systems, which may signal short circuits or overloads. Analyzing these events accurately allows for taking preventive measures and improving process stability and system safety. Background on indexing in TrendMinerTrendMiner uses indexing to enable fast, interactive visualization and analysis of time-series data. When a tag is accessed for the first time, it undergo

Often, we want to analyze or report on key KPIs, such as consumption, production, average temperatures, or maximum values of critical variables. However, these data need to be analyzed separately based on the recipe they correspond to.In TrendMiner, it is possible to unify all workflows so that reports for multiple recipes can be obtained with a single process. This is due to the ability to include the “constant” condition in the Value Based Search and to add string variable calculations. Here’s how it is done:Prepare the View: Load the tag indicating the recipe name and the rest of the necessary tags to create the report. Perform the Search: Go to the search menu and start a value-based search. The condition will be: Recipe name tag CONSTANT. The results obtained will correspond to the time period indicated in the context chart. Add Calculations to the Search Results: String Variables Calculation: Start value of the recipe name. This calculation will indicate which recipe each of t

Background:TrendMiner's "Event Analytics" is typically used for batch processes, but it can also optimize continuous processes. By breaking down the data into manageable hourly intervals, this approach provides detailed monitoring and identifies optimal conditions for enhanced efficiency and productivity.Steps: Preparation: Add the most important process parameters. Include the pre-installed TM_day_ tag. Data Splitting: Use the value-based search feature to segment data. Set the condition to TM_day_ constant. Ensure a minimum duration of 59 minutes. Adding Calculations: Add calculations on the search result. Example calculations: Average Temperature, Integral Cooling Water, Minimum Pressure. Event Analytics: Use the 1-hour aggregated data within Event Analytics. Analyze the data using histograms or parallel coordinate plots to visualize and identify optimal process conditions. Picture 1: This parallel coordinate plot from TrendMiner’s Event Analytics shows the relationship b

BackgroundOften 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

We all love the monitor feature in TrendMiner, however sometimes it can also be annoying when the monitor is triggered too many times and creates an email spam. In this article we will discuss how you can prevent an endless stream of TrendMiner monitor alert (emails) and just get an alert when a real event occurs.1. Use search results as indication for number of alertsA TrendMiner search is often the backbone of a monitor and thus we can use the number of search results as indication to the amount of monitor alerts we will get within the search period. For example, if we perform a search with a context bar period of 6 months and get 15 results, then we know that when we apply a monitor with this search we will get 15 monitor alerts within 6 months.2. Finetune your value based searchWhen you use a value based search the first thing you can tune to optimize your monitor is the minimal duration setting of your value base. In this example we want to know for when our flow out of our pump i

In this article, we present 4 of our least used but valuable features which you can use to your advantage. We also show some concrete examples. 1 - Operating Area Search Empowers users to intuitively identify optimal and suboptimal operating conditions through a visual interface.  Helps users detect process irregularities early by analyzing correlations between parameters.  Provides preventive maintenance warnings using the operating area search in a combination with monitors.  In the example shown below, the power a conveyor belt is consuming is plotted versus the specific power consumption, which takes into account the mass the conveyor belt is transporting. The scatter plot itself shows that there is an optimal point of operation looking only at energy consumption. Now, this area is selected as area of good operation and is used in the operating area search to look for periods when this correlation is changing, indicating a change in the operating conditions of the belt which me