Launch of SIMCA-online 16

SIMCA-online 16 News

SIMCA-online is a real-time process monitoring solution that helps you to get an overview of your production. It helps you to improve yield, increase throughput, reduce quality variation and ensure the final product quality.

With the advised future functionality you will be able to predict the final output and correct deviations to your process before it effects the final output of the production.

News in SIMCA-online 16

The web client has been updated to enable investigations and comparison of new, recent and historical production.

 To mention a few updates that has been made:

  • New start page with an overview over the production, units and alarms
  • Compare batches and production
  • Possibility to look at historical data by importing old batches
  • Buttons added for alarms and batches

The user interface for the desktop client has also been updated and new panes and filters has been added to make it easier for you to analyze your data. This enables you to get a better overview of what is going on by exposing the right controls at the right time.

To support deep learning and machine learning a new Python pretreatment functionality is available. Any calculation available in Python can be used in SIMCA/SIMCA-online as a pretreatment to a multivariate model and a model created in SIMCA can be transferred to SIMCA-online.

In this release there is also an update to the administrable notifications, which enables an administrator to choose which alerts the team should receive by adding email addresses to the system. This makes it possible to stay on top of your production by alerting the right people at the right time.

Late data entry functionality has been added. This means that the data from a completed batch is visible in the production overview even though it is finished. This enables SIMCA-online to be used for Continued Process Verification and this will make it easier for you to get FDA approval.

It is now possible to monitor tags that are not included in the model for continuous processes in real-time.

Clamping has been added for both the desktop and web client to enable you to remove an outlier to be able to see a normal deviation even when there is a spike in the process.

Try out SIMCA-online 16 in our demo portal
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