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Time to value is a key metric directly impacting the bottom line—profitability. The longer it takes, the more value is lost. TrendMiner can reduce the time to value down to a fraction when proper steps are implemented. Engineers struggle daily gathering data from various sources, stitching event information with process data, and using dated technologies built for megabyte-scale data. All this is done in addition to meeting the baseline operation and production at a minimum.Here are three simple steps your organization can implement for faster time to value.Clearly communicate the objectives and goals The organization's vision must be communicated from top to bottom. There is a reason the organization has selected TrendMiner! Objectives of the project must be aligned with the vision. Engineers involved in the day-to-day must be fully aware of the desired goals. The Sponsor, Project Manager, and the end-user must feel that they are integral to the set vision.   Streamline the train

 In industrial data analysis, preprocessing sensor data is crucial for accurate results, especially when dealing with sudden, abnormal spikes. These spikes can distort your analysis and lead to incorrect conclusions if not addressed properly. In this article, I will show you how to eliminate spikes from your sensor data using four different methods in TrendMiner, ensuring that your analysis is reliable and accurate.Examples of spikes in sensor dataSpikes in sensor data can occur due to various reasons such as sensor malfunctions, temporary communication errors, or unexpected events in the process. For instance, a sudden spike in temperature readings from a reactor might be caused by a faulty sensor rather than an actual temperature increase. Similarly, pressure spikes in a pipeline could be due to momentary errors in measurement. Removing these spikes from the dataset ensures that the analysis focuses on the real data and not on these anomalies. Methods for getting rid of spikesOption

Are you looking to discover where TrendMiner can bring additional value to your organization? By following these steps, you can follow a method that is used by TrendMiner customers to identify a scalable solution to implement across multiple assets, lines & factories. Step 1: Identify a strategic processThe identified process should be equipped with the required sensors to capture the data needed for analysis and monitoring. Choosing a high-value process ensures importance within the organization. A process that is similar across multiple lines or factories is preferred as that increases the scale at which the solution can be deployed. Step 2: Gather expert insightsThe process experts of the identified process have extensive knowledge on how the assets should operate to achieve optimal results. Gathering and organizing a conversation between the process experts yields the information we need for the next step. Step 3: Define Process limitsOnce the ideal operating zones for the proc

👉🏻 BackgroundIn a water purification system, efficient sludge transport is crucial tomaintaining optimal operations. The system employs five conveyor belts,which are dynamically activated based on the sludge load. At any giventime, a minimum of one and a maximum of four belts may be inoperation. However, the dynamic nature of this system introduceschallenges. If one of the belts malfunctions or operates inefficiently, it canlead to increased sludge accumulation, potentially disrupting the entirepurification process. To prevent this issue, a robust monitoring solution isessential to ensure that all belts function properly, regardless of the load.🕵 ChallengeMonitoring the operation of the conveyor belts is complicated by thevariability in the number of active belts. This dynamic operation makes itdifficult to determine when a belt is malfunctioning versus when it issimply under a different load condition. The challenge lies indistinguishing normal variations in performance from actual

Are you a project manager or sponsor and want to lead the way and make TrendMiner successful at your site? A successful project must have some clear goals to help you determine the right people and strategy to ensure its success. Rolling out TrendMiner at a new site or introducing it to a new group isn’t the exception.Here are 3 goals that can help drive a successful roll out.Reduce Process Variability and Cycle TimesConsistency is crucial for achieving high-quality production. One of the primary goals for any site is to reduce batch-to-batch variability and optimize cycle times. With TrendMiner, you can better identify key parameters that impact variability and make adjustments to your process (batch or continuous), leading to increased efficiency.Leverage Data from Multiple SourcesIntegrating data from various sources like LIMS, electronic batch record systems or logbooks and maintenance systems is crucial for achieving a comprehensive view of your operations. TrendMiner allows you t

Background So, you've found yourself wanting to historicize something you've observed in TrendHub. As the process engineer for the past two years, you've noticed a clear pattern between unit swings and recurring filter change on a feed pump. Now, you need to compile these findings into a list and annotate them on the trends. That is the only way you can convince everyone else that this is indeed the root cause of the swings and not just some random incident. Although you've briefly heard of ContextHub, once you reach this screen, you find yourself wondering, "What is a component, and what do you mean by Type???"  Component and Type are two parameters that must be assigned to create a context item, or a block of information linked to a data point or a period of data associated with an event identified in your datasets. The Component links your observation to a particular tag, while the Type assigns a category that can later be used as a filter in ContextHub.  Types There are several pre

Curious about selecting the right key users for your TrendMiner project? Empower the ideal candidates to drive impactful change and ensure seamless adoption. 🚀 Identify the right key users  Each new tool requires specific key user profiles outlining which people are most likely to quickly adopt the new way of working. Select the right people who fit the pre-defined profile, so they can enable and support other users to more quickly adopt - and get value from - the new way of working. The key users play a central role We will work with the key users intensively during the hands-on sessions to get them to know the basics of the software and create first value. Furthermore, we will stay in close contact with these users to expand their TrendMiner knowledge and skills, and to measure the progress of the project. To maximize the chances of successful onboarding, key users should adhere to and be selected based on the following profile.   The ideal key user…  … commits to accompany the pilo

 In industrial data analysis, it is often necessary to formulate complex conditions to achieve precise search results. However, it is not possible by default to combine AND and OR conditions within a value-based search in TrendMiner. TrendMiner allows you to combine multiple conditions in a value-based search, but you can only combine all conditions with either AND or all with OR—not both simultaneously. Here, I will show you how to effectively combine AND and OR conditions in a value-based search.Examples of combining AND and OR conditionsA typical example would be searching for production data where multiple products (e.g., ALPHA and BETA) are analyzed under specific temperature conditions. Other examples include identifying production phases where certain machines are either in "Standby" or "Maintenance" mode, but only if energy consumption is below a defined threshold. Another example could be analyzing phases where specific chemicals are either in a "Mixing" or "Reaction" state, b

  Background Monitoring thresholds is a common use case in the chemical industry, essential for maintaining consistent production quality and ensuring operational safety. Thresholds act as predefined limits, signaling potential issues in the process when exceeded. Failure to effectively monitor these thresholds can lead to production inefficiencies, equipment damage, and reduced product quality. Such deviations can be caused by factors like temperature fluctuations, pressure variations, or torque instability, as well as unexpected changes in raw material quality. TrendMiner provides an effective solution by enabling reliable and continuous monitoring of these thresholds. ChallengeThe challenge in monitoring thresholds lies in precisely defining and continuously tracking them. TrendMiner offers a solution by enabling users to set up monitoring through value-based searches, which can trigger automatic alerts. Additionally, the creation of context items can be activated to allow for detai

If you ever downloaded TrendMiner from our file server you might have noticed there are a lot of files on there. The .tar.gz files are the actual TrendMiner installation/upgrade packages. The .zip file is the connector installation/upgrade package. But do you know what these .md5 and .sha1 files are? md5 and sha1 are 2 different cryptographic hash functions. A cryptographic hash function is a mathematical algorithm that takes an input of any size and produces a fixed-size, unique output (hash) that appears random. It is designed to be secure, meaning even a small change in the input drastically changes the output, and it is computationally infeasible to reverse or find two different inputs with the same hash.TrendMiner provides the hashes of the installation packages for you as a customer to verify that the file you downloaded is identical to the one which is hosted on our server and the file was not corrupted during download.How do you do that?Download and open the .md5 from our file

Sometimes, for better visualization and monitoring, it is helpful to represent the durations of certain important events in the plant within a variable. This is possible in TrendMiner by following a couple of steps.First, it is necessary to create a slope tag, from 0 to 1, that connects the start and end points of the event.This can be done with a conditional formula and time changes. For example, an event from the moment a batch starts until the “Phase 3” starts: It is important that the obtained variable consists of constant slopes from 0 to 1 and from 1 to 0. We do not want it to remain constant at values of 0 or 1 for long periods, as this could affect the second step of the workaround. This is why time shifts are used, indicating only the exact moment of start and end.Secondly, we need to transform the slope tag into another variable that indicates the duration of each slope. This is done with the formula 'if((a-b)>0,1/(a-b)/60,,0)' following the explanation provided below (to

Communication and collaboration in the form of a user community has anchored itself as a powerful technique that enhances the overall experience for everyone, from users to admins to developers. User communities foster collaboration, serve as inspiration, propel innovation, harvest a support system, and enablement of users. How well the users engage in the community can amplify the success of an organization. Here are at least four reasons to bring users to the TrendMiner community.Share knowledge and expertise. Every user brings a unique insight that can help the organization achieve its OKRs (objectives and key results). In a shared community space, everyone can tap into this resource and reap the benefits. It is not uncommon that users in different plants or business units and even in other organizations are facing similar challenges. By sharing these challenges, a solution can be reached faster and inspire new ideas.  Sense of belonging and support. Plant life can be busy and probl

BackgroundIn one of the distillation units, one of the product temperatures is being lower than expected for around 1 year, leading to lower product recovery, as the separation is not as efficient as it should. This means a 10% recovery loss in the company, which is an important economical loss. ChallengeTroubleshoot the causes for this deterioration in performance, by detecting the influencing variables and the respective influence of each. Solution-Load all the related tags, as well as the key temperature-Run the correlations engine to find correlations against the potentially correlated variables and against all the variables of the asset-Layer 2 periods (high and low recovery) and compare statistics and trends of the potentially influencing parameters Results and value-Two process variables were identified as the main influencing factors. -It was identified that both variables weren't acting at the same time, but separately. That's why by themselves, the correlation is not to high,

BackgroundAs a process engineer, understanding the relationship between two variables is crucial and often necessary. For example, how does tower pressure impact overhead rates? How does temperature affect conversion? Operations are constantly making adjustments, and process engineers need to grasp the impact of various levers or handles on final product specifications, operating envelopes, and process safety. TrendMiner enables users to quickly analyze relationships between tags or variables, both visually and quantitatively.Scatterplot of natural gas usage vs carbon emissions.Steps to Analyze Relationships in TrendMiner:Step 1: Add the tags you are interested in analyzing to the active tag list for bivariate relationships.Step 2: Switch to the Scatterplot view.Change view from “Trend” to “Scatter”.Step 3: Adjust the time period to include relevant data for your analysis.Step 4: Evaluate the relationship. Use the scatterplot to qualitatively assess the relationship between the variabl

A broad implementation of TrendMiner exponentially increases the value your organization can get from our product. If more people are using TrendMiner, more people can collaborate, learn from each other and in the end, it will be easier to maintain knowledge inside the organization. Therefore, it is crucial to ensure that new employees know about all the relevant tools used.  There are several ways to make TrendMiner a part of your onboarding curriculum. Here are some tips:  Make a checklist of all the onboarding steps, including the different important tools which are being used.  Explain clearly why TrendMiner is important for your organization.   Make sure new employees have immediate access to TrendMiner.  Interactive Workshops: Organize sessions where new hires can practice using TrendMiner with real examples from your plant. Provide access to our training videos, documentation, and best practices guides that they can refer to as needed: https://userguide.trendminer.com/?lang=

Here's how TrendMiner can be utilized at each stage:Define: Use TrendMiner to define the problem or opportunity by analyzing historical process data to identify trends, patterns, and areas for improvement => Getting started with TrendMiner Collaborate with stakeholders to establish clear project goals and objectives. Measure: Utilize TrendMiner to collect and visualize real-time and historical process data from various sources (Time series, Context and Asset data). Measure key performance indicators (KPIs) and baseline process performance to establish a benchmark for improvement. Analyze: Apply advanced analytics and visualization tools within TrendMiner to analyze process data and identify root causes of inefficiencies or deviations. Use TrendMiner's self-service analytics capabilities to empower subject matter experts and process engineers to explore data and generate insights independently => Enable them to become data engineers with TrendMiner, even if they're not data e

Our recent release webinar recording is now available. You can watch it to see detailed explanations and demos of the latest TrendMiner functionalities.  We encourage you to visit this community post and vote for your favorite functionality or share your feedback in the comments.

If you notice that a certain tag in TrendMiner is displaying data that might be incorrect, you can use the PlantIntegrations API to check which tag data is being retrieved from the historian.If the data in the historian corresponds with the data in TrendMiner, the faulty data is already present in the historian and should be rectified there.To access the PlantIntegrations API you can do the following:Open the IIS server on which PlantIntegrations is installed. Open the IIS manager and click on the PlantIntegrations website. On the right side of the screen you can now choose the ‘browse’ option which will lead you to the API.  This will lead you to the following API page: To perform an index call here you need the following information:Tag name Historian name Tag type Interpolation type Start- and enddate of the period you want to request Number of intervalsYou can find an example of an index call below in which the parts in green need to be configured depending on the call you want to

In our 2024.R1.0 release we introduced an additional layer of security, meaning an OTP code is mandatory to use the Admin account. (for ConfigHub and TrendHub login)You can read more about this in the article from Jef Vanlaer here.While trying to authenticate with the Admin account, I ran into following error message:  Invalid authenticator codeI found out that the root cause of this error is due to my TrendMiner server time not being in sync, thus the server thinks that the code I am providing is long expired/not valid yet.  After resolving the NTP issue my Admin login is working without issue again.

In our latest release, 2024R2, we’ve enhanced the Scatterplot display in TrendHub to visualize all layers of a TrendHub view, not just the base layer. This new feature enables you to compare relationships between different tags across multiple layers, making it a powerful tool for troubleshooting, root cause analysis, performance grading, and more. In this article, we'll walk you through how to use this new feature to its full potential.Step 1: Adding Different LayersThere are several ways to add layers in TrendMiner. In our example, we used value-based searches to identify high- and low-quality batches and added the three highest quality and three lowest quality batches as layers.Overview of all the layersStep 2: Switching to Scatterplot ViewBy changing the plot visualization to a scatterplot, you’ll immediately see the option to create a multi-layer scatterplot.Scatterplot visualization with multi-layer enabledStep 3: Customizing Your LayersClicking the “Customize Layers” button open

As you might already know TrendMiner provides some support scripts to make some tasks easier. Today we have 5 official support scripts: batch indexing: indexes the tags in a given list indexing performance testing: benchmarks the indexing performance provided by a historian at specific index resolutions listing tags in a historian: lists all tags available to TrendMiner for a specific historian listing indexed tags: lists all tags currently indexed in TrendMiner cleaning indexes: clears the index of those tags that match the provided criteria All details can be found in this documentation article: https://documentation.trendminer.com/en/support-scripts.html But next to these scripts you can also leverage the TrendMiner APIs to write your own script in your favourite language. For example: clean all indexes of a list of tags provided via a .csv file.Did you write your own scripts already? Which scripts would you like to see productised in TrendMiner? Let us know!

When was the last time you had a TrendMiner HealthCheck?You wouldn't drive your car for years without an oil change? Or skip your annual physical? Just like your vehicle and your body, you need a TrendMiner HealthCheck to ensure peak performance for your data analytics. What's a TrendMiner HealthCheck?Think of a HealthCheck as a tune-up for your TrendMiner implementation. It's a dedicated session with your Customer Success Manager and Data Analytics Engineer to review new features, optimize your current setup, and ensure you're squeezing every drop of value from our platform.How Can a TrendMiner HealthCheck Supercharge Your Analytics?Discover hidden gems: We're constantly rolling out new functionalities. Your CSM will showcase the latest and greatest, tailored to your specific needs. Optimize your workflow: Are you taking the scenic route when there's a shortcut available? We'll help streamline your processes for maximum efficiency. Align with best practices: Learn how industry leaders

Creating clear and effective graphs is a vital skill for anyone involved in data presentation. In process engineering, the ability to visually convey complex information can significantly enhance the impact of your work. However, not all graphs are created equal. Poorly designed graphs can mislead, confuse, and obscure the very data they aim to highlight. This functional tip outlines essential best practices for making enhanced TrendHub views that are both informative and visually engaging. By following these guidelines, you can ensure your graphs not only accurately represent your data but also resonate with your audience, facilitating better understanding and decision-making. Keep It Simple: Avoid clutter by minimizing gridlines unless they are necessary.     Try to avoid displaying excessive context items unless they are needed to emphasize a reoccurring issue.   Consider whether all data actually needs to be displayed in the focus chart, or if keeping longer-range data i

 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

 Background Fluctuating process parameters in the chemical industry present a significant challenge as they can impact the efficiency and quality of production. These variations can be caused by inaccurate measurements, unstable raw material quality, or insufficient process controls.For instance, Torque fluctuations in machinery may lead to mechanical damage, compromising operational safety. Temperature fluctuations in reactors can affect reaction kinetics, resulting in inconsistent product quality. Likewise, pressure fluctuations in pipelines or reaction vessels can affect product consistency and equipment safety. ChallengeManaging fluctuating process parameters may require setting and monitoring thresholds, tracking the range of variations, and creating context items. TrendMiner simplifies this by allowing users to define and oversee limits, measure fluctuations, and visualize all relevant data on a dashboard.  SolutionDefining upper and lower limitsIn this step, upper and lower torq