Case Study
- Melchior Krijgsman
- Jun 30
- 2 min read
Updated: Jul 4

About the client
โ๐๐ฆ ๐ข๐ณ๐ฆ ๐ช๐ฎ๐ฑ๐ณ๐ฆ๐ด๐ด๐ฆ๐ฅ ๐ธ๐ช๐ต๐ฉ ๐๐ฏ๐ต๐ณ๐ฐ๐ฑ๐ช๐คโ๐ด ๐ข๐ฃ๐ช๐ญ๐ช๐ต๐บ ๐ต๐ฐ ๐ฆ๐ฏ๐จ๐ช๐ฏ๐ฆ๐ฆ๐ณ ๐ช๐ฏ๐ฏ๐ฐ๐ท๐ข๐ต๐ช๐ท๐ฆ ๐ด๐ฐ๐ญ๐ถ๐ต๐ช๐ฐ๐ฏ๐ด.โ Climax Molybdenum
Climax Molybdenum Company, a subsidiary of Freeport-McMoRan, is the world leading molybdenum producer and supplier. For their plant in the Port of Rotterdam, they wanted to research the possibility of increasing the energy efficiency and reducing CO2 emissions.
About the project
The challenge at Climax Molybdenum is to optimize the factoryโs energy efficiency by effectively utilizing available waste heat within its complex heat management system. The factory operates a mix of batch and continuous processes that generate and consume heat, subject to constant fluctuations. These processes involve 25 identified heat and cold sources/sinks, some of which pose difficulties due to factors such as corrosiveness and low temperatures. The goal is to maximize energy savings by integrating heat recovery and
utilization technologies, such as direct heat recovery, heat pumps, mechanical vapor recompression, organic Rankine cycle, steam turbines, and heat storage (molten salt, water, and steam), within the existing infrastructure.
Method
Entropic employed an iterative approach to develop a heat optimization model, using a digital twin of the factoryโs 25 heat and cold sources/sinks. The compact methodology
includes:
1. Data Collection: Gathered design requirements, reviewed prior studies, and
collected measurement data.
2. Data Preparation: Mapped heat sources/sinks, including challenging streams, and
cleaned data for accuracy.
3. Basic Heat Flow Model: Defined source properties, designed initial heat network
layout, conducted pinch analysis, and iterated for optimization.
4. Intermediate Heat Flow Model: Integrated dynamic loads and time-series data,
simulating operational scenarios.
5. Advanced Heat Flow Model: Built dynamic equipment models and simulated
technologies in the digital twin.
This iterative process, with regular factory feedback, ensured quality, adaptability, and tangible results, addressing technical challenges and maximizing energy savings.
Results
The study identified significant opportunities to reduce energy costs and enhance efficiency at the facility through targeted optimizations in two key systems:
System 1
โ Short-Term Opportunity: Integrating heat provides the quickest and most
substantial cost savings.
โ Savings: 294.609 mยณ of gas.
โ Carbon Emissions Reduction: 886 tons of COโ.
โ Long-Term Potential: Incorporating heat pump technology offers additional savings:
โ Savings: 237.501 mยณ of gas.
โ Carbon Emissions Reduction: 714 tons of COโ.
System 2
โ Short-Term Opportunity: Optimizing a drying process using simple heat
exchangers and non-corrosive fluids.
โ Savings: 166.343 mยณ of gas.
โ Carbon Emissions Reduction: 296 tons of COโ.
By implementing these short- and long-term strategies, the facility can achieve substantial energy and cost savings, improve energy efficiency, and significantly reduce carbon.
โWe were impressed with Entropicโs ability to scope innovative solutions at a conceptual levelโ




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