Founded in 2018 by Leopold Spenner. We use machine learning and control technology to predict the quality properties of cement and concrete and enable companies in the cement and concrete industry to optimize quality and production costs and reduce CO2 emissions.

In order to decarbonize cement and concrete, the challenge is to significantly reduce the proportion of clinker. However, this leads to higher quality requirements, increased labor input and therefore significantly more expensive concrete. As a result, the production of CO2-reduced concrete has not yet been profitable.

This is exactly where alcemy comes in with its two products for cement and ready-mixed-concrete plants: In the cement plant, alcemy enables continuous analysis of quality-relevant data from chemistry, mineralogy and particle size distribution. Using alcemy’s intelligent algorithms, quality parameters are then predicted, target values are calculated to optimize current cement production and continuously fed back to the control station.

In the ready-mixed concrete plant, the AI-supported software continuously forecasts the quality parameters in real time during production. The company uses existing data from the mixing plant (dosing events, concrete temperature and the active power curve in full resolution) and combines this with sensor data from the truck mixer (oil pressure, drum rotation speed or water addition). The information on how the concrete actually arrives at the construction site is fed back to the ready-mixed concrete plant and thus daily transport conditions are included in the forecast.

The information gained from this helps to closely monitor the concrete, identify optimization potential during production and ensure consistent quality even under difficult conditions. For example, the quality of the concrete can be guaranteed even with fluctuating raw material properties, different weather conditions and regardless of the personnel deployed.

Berlin, Germany

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