How do we create added value from your data?

A look at the pilot project of ControlTech Engineering's Data Science Framework shows that contextualization is of great importance when collecting and analysing data. Validated interpretation of the data is only possible with the specialist knowledge of everyone involved in the process. At the Siemens Pharma Forum 2024, we presented the results and lessons learned from the Data Science Framework project at the FHNW Institute of Chemistry and Bioanalytics.

“To Be Continued”—that’s how Stefan Kramberg, IT Systems Engineer at ControlTech Engineering AG (CTE) in Liestal, concluded his technical presentation on the topic of data science frameworks at the Pharma Forum 2023 on. It should continue, because the Data Science Framework The project had not yet been successfully completed. This caused some discontent. “We have a theoretical model, but not enough data,” admits data specialist and project manager Stefan Kramberg.

This was followed up. Stefan Kramberg: "We've done it! The data analysis helps us to optimise the manufacturing process." It was a challenge, because initially, the data available was to be able to carry out serious evaluations. The pilot project at the FHNW Institute of Chemistry and Bioanalytics involved a production plant that does not produce for the market. It could therefore be used for testing purposes in a flexible manner.

The objective was clear: the ethanol-water mixture was to be separated into ethanol and water, with ethanol being the product and water the waste product. The brief for FHNW's pilot project was for ControlTech Engineering (CTE) to achieve a cost reduction by reducing consumption of steam, coolant and nitrogen. The aim was also to increase quality. To this end, product purity was measured via the density of the distillate.

First results with added value

After 15 further test runs, exciting data is emerging: The data science framework is working and it's delivering considerable added value for production plants. Finally, the results are there. Years of collected data can now be profitably optimised. Stefan Kramberg: "We use the model to detect anomalies and uncover contradictory data. Based on the appropriate context, economic interpretations are created. In this case, collaboration with the process experts is important. This is the only way we can clean up the data and visualise each individual production run based on measured variables. This creates comparisons and long-term added value from the data." Using the data that has been collected over many years in an advantageous way is a complex task. However, Stefan Kramberg is convinced that if you don't start today, you'll miss out on great future opportunities in the industry.

Photo of Sascha Zeller, Business Unit Manager for Data Management at ControlTech Engineering AG.

Do you also have complex tasks to solve? Then allow us, together with you, to shed some light on your production processes.

Schedule a no-obligation consultation with Sascha Zeller, Business Unit Manager for Data Management.

"We at CTE can collect and analyse data, however, without context, there are anomalies that are not correct." In addition to the expertise of all those involved in the process, a partner is also needed for cleansing, processing and applying statistical methods. Only then can the data analysis be interpreted correctly.

For this reason, CTE has brought in additional expertise: "At the moment, we are still in the middle of the workshop. Data has been collected and is plausible. With a demonstrator, we now have variables that help us to achieve the customer's (FHNW) goals." How this works and more detailed findings were presented at Siemens' Pharma Forum 2024.

Read the presentation now

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How do we create added value from your data?

First results with added value

Do you also have complex tasks to solve? Then allow us, together with you, to shed some light on your production processes.

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