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We are currently using the trendminer‑interface SDK  to create and populate custom tags (e.g. predictions / calculated KPIs). During implementation and testing, we have identified a major limitation that becomes critical at scale.When using: client.io.tag.save(tag_data_dict, index=False)to write data to an existing tag:Saving a new dataset overwrites existing historical data for that tag. It is not possible to append new time‑series data to an existing tag. Writing data for a new time range clears previously uploaded history.Although the documentation refers to this operation as an “update”, the actual behavior is a full overwrite of the time series, not an incremental append.Why this is a problem?Because appending is not supported, every  update would require:Re‑uploading the entire historical dataset for each tag Maintaining full history externallyThis leads to:Significant performance and bandwidth overhead Long execution times High operational risk (partial uploads or failures can w

I am looking for an advice.We have a SQL Server database that records the various compositions of the daily raw feeds to upstream units for each of our plants. The data is therefore by definition time-series and indexed by plant, unit name and raw feed type with a value of volume/day.Because these data items are related, there would be a natural fit with context items and fields.. They could also be ingested as individual tags with a unique naming convention by plant, unit, raw feed type.Our primary objective is to troubleshoot and perform root cause analysis for issues observed on downstream units based on the various daily raw feed blends. This definitely involves time shifts and also value-based searches + event analytics.Even though the data is naturally organized as event frames or context items, I am inclined to prefer ingesting this data as individual tags to enable diagnose/cross-correlations, event analyses and possibly fingerprint, unless there is something I am missing with

Dear AllI’ve already deployed the pmml in MLHub but when its success. There’re no ML Tag for creation in Trendview. Does anyone found same problem?

cant sign in to trend

Hi everyone'sI’m the beginner use python for ML, Please help me i can't connect View_ID. the error massage show code 404  how can i do.

We have a SQL database that continuously collects equipment downtimes along with associated characteristics/properties including, obviously, start and end timestamps. Being able to view these as context items and perform analyses against historian tags that are already accessible as other data sources in Trendminer would be very valuable. Is it possible to:1- Import existing event records from SQL Server in Trendminer as Context Items2- Establish a connection to continue to collect these moving forward?

Simple, possibly stupid question: If I want to have a linear regression of a single tag e.g. BA:TEMP.1 against time, how do I do this?

We are upgrading to R4 and want to take advantage of the ability of sharing folders with groups for published/official applications in addition to having personal folders.We have 13 plants and likely 15 process equipment type folders per plant which is what we are planning to use for hosting the applications. This adds up to approximately 200 folders to createI do not seem to be able to create a set folders for a plant to make a bulk copy and paste into another plant. Am I missing something or is there a way to do this?

Hello,  I want to create an if formula that returns text instead of a number, like this: if(a=1, “Phase 1”, “Phase 2”) When I try I get an error message but I’m not sure if it’s because it’s not possible or just the writing nomenclature.  Thanks! 

 I could make a workaround, for example by doing the division in the same tags as the summation. But just wondering.

A trend was shared with me and I need to share it with others but I don't see the an option for this under the actions drop down on top right of screen.  Any step by step guidance available?

Dear AllIf it possible to excess the Monitoring more than 10.  

Hello,I am currently developing a dashboard to monitor the nitrogen consumption of our production lines. Each line consists of several machines connected to nitrogen tanks, and we have flow measurement devices for each machine. I have defined two types of anomalies for these machines:Nitrogen consumption when idle: to detect unintended leaks. Nitrogen overconsumption when running: to detect deviations from normal flow.For this purpose, I have included two surveillance tiles for each machine in the line-specific dashboard. However, my goal is to create a high-level dashboard that provides an overview of all lines, showing if there is an issue with any particular line. From there, users could click a link to access the detailed dashboard for that line.My question is: Is it possible to monitor from the general dashboard whether anomalies are occurring on the lower-level dashboards? The searches I use for the detailed dashboards are based on conditions like “over X value during Y minutes,”

This machine learning model can't be saved because it exceeds the maximum number of allowed levels (2) in a machine learning modelAnyone has faced this problem from mapping the tags to the PMML Model.The tag that be calculated from the Aggregation after that using in formular tags. 

Of a fermentation batch I have successfully created a search and fingerprint (based on layers) of the productivity. I have a request to visualize this fingerprint on the current running batch in a dashboard (to be shared, and should require no intervention).How can TrendMiner know when to “reset” the view timeline whenever a new batch is started. I do have another tag of the program sequence (recording when a step is changed and therefore when a batch starts and ends, is recorded as an analog signal) which could be used, but I don’t know if and how that could work. Can this work, * without * any manual work dragging the fingerprint over the running batch?

I’ve made a new tag from a value since the output was in “TONS”. So I made one that converted 170 TON into 170000 kg. Only the kg’s isn’t showing at the end. It’s just the number. Is there maybe a way where you can add the “kg” at the end of a converted number?

Regarding embedding a Notebooks output into a DashHub tile via the “Pipeline” feature as an Expert license holder, I am wondering what the limit specs are for bridging the Notebooks/DashHub environments.  I was testing out the Pipeline feature to embed a visual output, specifically a plotly chart, from my Notebooks script into a tile in DashHub. I pulled in a saved View with two tags, converted them to a dataframe on a one-minute granularity, so about half a million data points (they only have data for 2025), and I am able to succesfully plot these tags in a Notebooks output. However, when I publish the notebook to a Pipeline and configure a “Notebook output” tile in DashHub, it loads for ~10s then fails with the error message: “The notebook pipeline is too big to be run by a kernel and cannot be loaded.” In my Notebook script, for reference, the View loads into the dataframe in about ~120s, which doesn’t seem overly ambitious, so I am wondering at what point the dataframe is too large

Is it possible to add aggregation results in a context table? For example, I would like to have a table with all the cleaning registered in the last month with the resources consume such as water, chemicals, steam, etc. I can calculate the volume of these resources consumed with the integral aggregation, however I cannot add them in a context table. How can I add it. Column of water added for explanation proposes.  

I was sharing the Trendminer dashboard with my colleague, and he asked me a question about whether Trendminer can review the Dashboard and automatically generate a report. This explains any anomaly and some other critical aspects of the machine or system performance based on the dashboard data. Currently have the capabilities to use the trigger of a message or email, looking for reporting that highlights of the last 24 hours (or longer duration). 

When I have a value based search I can add the result of the events also to a context item (a calculated item).On the moment I create a monitor out of this, the events are created, but I can not map it to a context item. For more information see the attached document.

Hey, we are using conditional coloring of CH views a lot. Is there a way that we can deploy color coding rules by the SDK?We would like to apply the same rules on multiple values and manual configuration is quite time consuming and quite error prone. BestSören

Hi allIs there a way to quickly navigate to the formula editor out of the TrendMiner View Tag dependencies?How I do it now? I open the Tag-Builder, click on saved formulas, search for the formula and edit it.It would be helpful to be able to open the editor directly from the view. BR Peter

Hey, do you have experience with control charts in TrendMiner? We are thinking to set up some control charts for our batch process. As example we would look at avg temeratures at a certain step of a batch: Would this be doable with MLHub? If yes, do you have example code you can share?This would be very helpful for us to test it shortly in TrendMiner. Best​​​​​​​Sören

I have data which is coming over as analog, but I need to treat this data as step data in calculations, trends, searches, etc.  Is there a good method to accomplish this, as I am unable to change the data type from the historian? 

We experience that we are not able to register for upcoming training events as an error occurs now for some days already. Anybody else experiencing this?