In a rapidly evolving landscape of energy efficiency solutions, BeChained stands out as a niche player, offering a specialized focus on energy efficiency for production factories.
While competitors, i.e. Enel X, ABB, Siemens, and other conglomerates, provide end-to-end solutions, including hardware sales, BeChained’s unique proposition lies in its dedication to optimizing resource control in industrial environments.
Automatic decision making is only based on data, gather in real-time from the factories, so it is hardware agnostic.
For this, BeChained exploits state-of-the-art Artificial Intelligence models to make and execute automatic decisions in production.
This strategic focus positions BeChained as a leader in preparing for demand-response opportunities, from demand-side energy flexibility.
The BeChained’s Advantages:
- Laser Focus on Energy Efficiency:
- Unlike competitors offering comprehensive energy management solutions, BeChained excels in a niche — energy efficiency in production factories. This singular focus allows BeChained to delve deeply into the intricacies of industrial processes, delivering tailored and impactful solutions.
2) Reinforcement Learning Multi-Agent Technology:
- BeChained’s cutting-edge AI technology is based on Reinforcement Learning (RL) with a multi-agent approach. RL enables the system to learn optimal control policies over time, ensuring dynamic adaptability in complex industrial environments.
- The multi-agent system facilitates collaboration among different components, enhancing the overall efficiency of the solution.
3) Real-Time Optimization and Execution:
- BeChained’s solution doesn’t stop at identification or suggestion.
- It goes a step further, by executing improvements in production processes in real-time.
- This instantaneous response ensures that the identified optimal settings are not just theoretical, but are actively contributing to energy savings and operational efficiency.
- These improvements are directly executed in production, dialoguing with Manufacturing Execution System through industrial standar protocols, i.e. SCADA.
Steel plants are capital-intensive, long-lasting assets that typically operate over 40 years. That is why it is vital to ensure that best available technologies are used in all key production processes at the time of construction or during major upgrades. In new and existing production facilities and equipment, efficiency can be improved by:
- optimising processes through better controls and monitoring…
- integrating artificial intelligence to enhance productivity
4) 19% Energy Efficiency Improvement:
- BeChained boasts a remarkable 19% improvement in energy efficiency for its clients, significantly reducing energy costs and carbon offset spend.
- This quantifiable impact sets BeChained apart, showcasing the tangible benefits of its specialized approach.
The European Commission estimated that the economic potential of reducing final energy consumption by 2030, compared to business as usual, is of 16 % for the commercial sector and of 23.5 % for industry
Note: The European Commission study “Technical assistance services to assess the energy savings potentials at national and European level, Summary of EU results”, February 2021.
- BeChained is not that far from the EC target, and to reach it and go beyond, it focuses on the state-of-the-art of technology for decision making and a multi sector approach.
5) Multi-vertical approach
- BeChained tackles non-core processes in industrial manufacturers, whether water management, exhaust or dust treatment, compressed air or HVAC and others.
- They do not pose a risk the day to day business (production).
- They are common throughout different sectors, i.e. from steel to paper making, food and beverage processing.
Clarifying the AI Landscape:
In the midst of the AI hype, where confusion often reigns from basic machine learning to advanced deep neural network models, BeChained stands as a beacon of clarity.
The key differentiator lies in the use of Reinforcement Learning for energy efficiency optimization, as opposed to traditional machine learning approaches.
Energy Efficiency: Reinforcement Learning vs. Machine Learning:
- BeChained’s Reinforcement Learning excels in dynamic environments where decisions are sequential and impact future states. This aligns seamlessly with the continuous and evolving nature of industrial processes.
- Traditional Machine Learning, on the other hand, might struggle to capture the dynamic interplay of variables and adapt in real-time, making it less suitable for the nuanced requirements of energy efficiency in manufacturing.
Future enhancements leveraging Transformer Models and DeepAR:
BeChained is planning the enhancement roadmap with new technology stack.
- Transformer Models:
- Transformers (the “T” in ChatGPT) bring a unique set of capabilities to the table, particularly their attention mechanisms that can capture long-range dependencies in sequential data. This is crucial in understanding the intricate relationships within industrial processes, enhancing the efficiency of BeChained’s solution.
2) DeepAR for Probabilistic Forecasting:
- DeepAR’s probabilistic forecasting provides a crucial layer of understanding uncertainty in predictions. In the industrial landscape where system dynamics can be complex, having a model that accounts for uncertainties enhances decision-making and overall optimization.
In conclusion, while conglomerates offer holistic solutions, BeChained’s strategic focus on energy efficiency through AI-powered Reinforcement Learning sets it apart.
With quantifiable results, real-time execution, and a commitment to innovation through Transformer models and DeepAR, BeChained stands at the forefront of revolutionizing energy efficiency in industrial production. As the industry evolves, BeChained remains dedicated to pushing the boundaries of what’s possible in the realm of energy efficiency.
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