Pharma / Chemical

Merck KGaA reduces electricity use for cooling by 21% in an optimized system segment

<1 year
amortization period
21 %
average reduction in electricity use for cooling
Darmstadt, Germany
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At its headquarters in Darmstadt, Germany, Merck KGaA achieved a 21% reduction in electricity use for cooling in one optimized system segment during the first three months of autonomous operation. By introducing AI-based optimization into its existing cooling infrastructure, Merck improved the coordination of chillers, pumps, and cooling towers without construction work or interruptions to ongoing production. The project was implemented with etalytics’ etaONE® software platform.

For pharmaceutical and life sciences manufacturers, maintaining reliable cooling while improving energy efficiency is a significant operational priority. Merck's project demonstrates how energy efficiency in pharmaceutical manufacturing can be improved by making better use of existing infrastructure while maintaining production continuity.

This success story is based on the published press release: Merck Cuts Cooling Energy by 21% with AI.

Initial Challenge

Merck KGaA's headquarters in Darmstadt, Germany, is its largest global research and production site. More than 12,000 employees work at the site, where over 25,000 products are manufactured across Healthcare, Life Science, and Electronics. The facility is also one of the company's largest energy consumers.

Cooling plays an important role in supporting these operations. More than 20 million cubic meters of chilled water circulate through the site's cooling systems each year.

As part of its commitment to reducing CO₂ emissions by 50% by 2030 compared with 2020 and achieving climate neutrality by 2040, Merck sought further opportunities to improve energy efficiency. The challenge was to reduce electricity consumption within its existing cooling infrastructure while maintaining the reliable operation required across the site.

The Solution

To improve cooling efficiency, Merck KGaA worked with etalytics to optimize the operation of its existing chillers, cooling towers, and pump systems using the etaONE® software platform.

The project team identified opportunities to improve water flow at a hydraulic separator and make pump operation more efficient under partial-load conditions. Using a pressure-based model of the cooling system, the software calculates coordinated operating setpoints, which are transmitted to the existing building automation system.

Operational reliability remained a priority throughout implementation. The optimization operates within defined limits, with automatic fallback to conventional control if required. Operators can also intervene manually at any time.

Following an initial test run in March 2025, Merck transitioned the optimized cooling-system segment to autonomous operation within two weeks, without construction work or interruptions to ongoing production.

Measured Results

  • 21% average reduction in electricity use for cooling in the optimized system segment within three months compared with previous operation
  • No modifications to the existing infrastructure were required
  • No disruption to ongoing production processes

These savings were achieved solely through improved control logic and system coordination. The project contributes directly to Merck’s sustainability targets.

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What's Next

Further enhancements are already in preparation. Merck and etalytics plan to extend the optimization to additional cooling assets and integrate predictive maintenance use cases, starting with automated cleaning recommendations for cooling tower filters.

In Collaboration With

The project is part of EISKIG, coordinated by the ETA research group at TU Darmstadt and funded by the German Federal Ministry for Economic Affairs and Climate Action. Within the project, Merck provides real-world application scenarios and system data, while etalytics delivers digital twin models and optimization logic. The collaboration between Merck and etalytics will continue beyond the scope of the EISKIG project.