25th of April 2023
The 2023.R1.0 release contains the following new functionality and improvements:
Innovation Highlights
- Digital Twin Manager: Build and manage your operational digital twin by setting up your asset hierarchies and building up your organization's data fabric by attaching your tags, relevant events (batches, downtime, quality samples,...) and predictive machine learning models, as well as managing appropriate access permissions.
- Search result refinements: Enhance ad-hoc event analysis by exploring subsets of search results based on duration and calculation values. Users can simultaneously view refinement boundaries; calculation and duration value histograms; and how refinements affect distributions. This new capability enables users to:
- Define more appropriate boundaries, revise the search, and adjust a monitor’s sensitivity.
- Create context items over a specific subset of events defined by more than one calculation.
- Identify anomalous values more easily using the visual representation (histogram).
- Plug ‘n play connectivity to AWS IoT SiteWise to bring machine sensor data to TrendMiner, accompanied by asset structure and alarm data from the AWS platform.
- Plug ‘n play connectivity to Amazon Timestream to connect TrendMiner with all your timeseries and configured dimensions.
- Plug ‘n play connectivity to Microsoft Azure Data Explorer (Kusto) to pull time series data into TrendMiner.
Application Enhancements
- An overview of your “favourite” items in the work organizer.
- The last updated parameter of an item in the work organizer now indicates whether the item has been created or updated together with the date and time of performed action.
- Improvements to the restore last session option which now works better with saved items, allowing you to recover a lost unsaved existing view with its unsaved changes.
- ContextHub Multi-scatter plot performance improvements.
- ContextHub Gantt chart improvements – easily add context items with the most recent timestamp, by using the provided space on the right most side of the chart.
- Context fields are now ordered alphabetically in the context item.
- MLHub (Machine Learning Hub) notebooks can be opened directly from the Work Organizer.
- DashHub Text tile now comes with a smaller footprint to use it as a section header, and a larger edit mode panel.
- The DashHub value tile now also contains the unit of measurement of the tag or attributes.
- Usability improvements for updating dashboard content to behave less glitchy.
- The dashboard grid was improved to allow easier movement and swapping of tiles.
- The way tiles move over a dashboard has been improved, no longer pushing other tiles into a direction to make sure your current tile placement is not undone.
- Tiles can swap places when moving them, simply hover with you tile on another one. If the tile “fits” on the space of the moving tile, it will swap.
- The expire time of being logged into the application has been increased from 30 minutes to 24 hours by default.
Bug Fixes
- DashHub:
- Dashboards are now able to include 100 tiles.
- MLHub:
- Message fixes when notebook is saved or 'unsaved changes' remain.
- Alert when creating duplicate names.
- Notebook editor resizes with window.
- Code snippets are added underneath selected cell.
Patch Release Updates
We release patches periodically. To receive email updates on TrendMiner patch releases, subscribe via this link.
Known Limitations
- Embedding TrendMiner in external applications is limited to Microsoft teams. Extensions to improve this functionality and make it more robust coming later.
- External content tiles in dashboard need cookies to properly load all content (and be able to login when required).
- Scooter values may change when zooming in after adding the scooter. This is because scooters currently interpolate the data points on the chart.
- When calculated tags are deleted, they cannot be created with the same name again.
- After renaming a calculated tag linked to a context item, the component of the context item is not updated correctly.
- The Jupyter notebook files and output objects are not backed up automatically by TrendMiner in this release. You can recover them from your VM (Virtual Machines) snapshots or upload them via the ‘import’ function.
- Notebooks can be shared with other users, using the work-organizer. All shared users have edit rights and the most recent change is saved. However, as there is no live update or collaboration modus, working with 2 users on the same notebook at the same time can result in undesirable behaviour.
- The action displayed on the right-side panel of ConfigHub when a service is restarted, is no longer visible.
Synopsis
Digital Twin Manager
The digital twin manager section located in the platform configuration of ContextHub now gives you the opportunity to create, set up and manage asset hierarchies as well as manage permissions and asset specific types.
You can now create new asset structures fully within TrendMiner by clicking on the “Add asset structure” button from the “Asset structure” overview and then selecting to use the “Asset tree builder” as well as specifying a name for your new asset structure.
Once you have created a new asset structure, you can add new nodes to the current level by using the provided input field and the corresponding plus button.
Time series data of interest can be searched for and attached to a node by using the search bar on the right and by drag and drop.
Note: Attached time series data appears in a blue box on the node.
Editing of existing asset structures via the “Asset tree builder” user interface is supported for structures created within TrendMiner as well as structures imported from a “csv” file.
Note: Editing of existing asset structures via the “Asset tree builder” is not supported for structures that are synchronised from external systems.
Note: Changes made using the “Asset tree builder” are automatically saved.
Search Results Refinements
The search refinement option gives you the option to further filter or select search results based on your added search calculations, duration, or similarity score in a visual manner. The visual representation makes it possible to dive deeper in your data and gain faster insights in your data to test hypotheses or find possible root causes.
The histograms give a visual representation of the data distribution but also allow you to quickly select a minimum and maximum for each listed item. When setting a new minimum and/or maximum each histogram is visually updated accordingly to show how many search results are impacted by the new min/max selection.
Favourites item in the Work Organizer
Favourite items allow you to quickly find the information and documents that are most important to you. To further facilitate your work, we have added another section called “Favorites” in the work organizer. In this section all your favourite items are combined, so you can access them easily.
You can mark an item as favourite by clicking the star icon within any of the work organizer tabs, even the "Shared with me" folder. To mark or unmark an item as a favourite, simply click on the star in the row of the item you wish to consider a favourite.
The favourite tab list lists all the items you have highlighted as favorite. From here, you can perform actions on these items such as deletion or moving them to another folder (pending permissions).
If you are the owner of an item, the permissions system allows you to perform actions on it. If someone created an item that is not yours and shared it with you (permission to view), you can ask them for certain actions. You can see the owner’s name in the column “Owner”.
Plug ‘n play connectivity to AWS IoT SiteWise
Тhe AWS IoT SiteWise provider presents means to pull timeseries, asset and context data from AWS IoT SiteWise into TrendMiner.
With the timeseries and asset capability of this new provider type the sensor data from AWS SiteWise can be pulled into TrendMiner as timeseries tags together with the asset structure they correspond to. Using the context capability, alarms from AWS IoT SiteWise can be pulled into TrendMiner as context items.
Plug ‘n play connectivity to Amazon Timestream
The Amazon Timestream provider enables TrendMiner to pull time-series data from Amazon Timestream.
Plug ‘n play connectivity to Microsoft Azure Data Explorer (Kusto)
The Microsoft Azure Data Explorer provider enables TrendMiner to pull time-series data from Microsoft Azure Data Explorer.