Epsilon Energy – energy management solution for manufacturing companies

The energy transition from fossil fuels to electricity poses significant strains on electricity grids and energy availability across Europe. As a consequence, Manufacturing companies are increasingly faced with high energy costs and energy volatility. They need a scalable and flexible solution that helps them reduce costs and increase the energy independence.

Strategies employed:

• Improve decision-making capabilities through advanced production scheduling models and real-time insights.
• Enhance energy efficiency and reduce electrical grid dependency by optimizing the energy mix and scheduling.
• Reduce CO2 emissions and increase use of renewable energy, in alignment with Europe’s sustainability goals.

Four elements are at the heart of our solution:

Automated production scheduling engine based on metaheuristic algorithm that increased machine utilization and reduced energy consumption per part, resulting in a 6.4% reduction in lead time and annual cost savings.

Energy optimization engine based on mixed integer programming for peak shaving and energy cost optimization, leveraging solar energy and storage systems to achieve a 15%-17% cost reduction on annual basis.

Monitoring dashboards for production scheduling and energy orchestration use cases allowing users to derive insights into optimal operational patterns and steer decision making.

The manufacturing sector, particularly energy-intensive industries such as chemicals, food and beverage, basic metals, building materials, and paper, account for a significant share of total energy consumption and greenhouse gas emissions. These industries face challenges in optimizing energy use, managing peak demand, and integrating renewable energy sources due to the stochastic nature of renewable energy production.

The Epsilon innovation project aimed to address these challenges by developing digital and analytics solutions that enable manufacturing companies to

• efficiently orchestrate production schedules,
• reduce energy costs, and
• minimize their environmental impact.

We successfully implemented use cases at Croom Medical and voestalpine, which demonstrated significant improvements in operational efficiency and energy management.