Industry: AI Region: Italy Transaction price: US$ 1 million Transaction method: equity investment
Project introduction:
A technology company in Italy has long served all aspects of services, technology and training in energy efficiency, predictive maintenance and predictive modeling. The company's accumulated expertise in the industrial field enables it to take important steps in the field of digital innovation and integrate services that apply machine learning and artificial intelligence to factory processes.
The company has developed a customized AI-driven energy optimization scheme, which is suitable for integrated processes and IT solutions (digital factories) and integrated energy systems and mobility (energy). This energy optimizer is an AI-driven software solution for optimizing combined power plants and industrial energy networks. With AI-driven insight, real-time data integration and predictive analysis, it has changed the way of energy management. Help the industrial sector improve efficiency, reduce costs and embrace sustainability. Through predictive analysis, real-time data and AI-driven decision-making, it helps the industrial sector to reduce energy costs, maximize efficiency and minimize environmental impact.
The working principle of the optimizer & A three-step process is adopted;
● Digitalization: create a digital twin model of the energy system, map assets and define operational constraints.
● Simulation: Run multiple simulations to identify efficient energy production scenarios.
● Forecast: Provide optimized energy allocation one day in advance to ensure energy utilization while minimizing costs and emissions.
Key features:
● AI-driven optimization: identify the configuration of energy production and balance demand, cost and emissions.
● Integration with Internet of Things and market data: Use real-time data from Internet of Things sensors, weather forecast and energy market to improve suggestions.
● Automated reporting: provide daily reports and actionable insights to optimize factory operations.
● Predictive maintenance: detect inefficient problems before failures occur and improve the reliability of the factory.
Successfully deployed in combined power plants and industrial facilities:
● By optimizing energy use and reducing waste, the profit rate is improved.
● Natural gas is saved and fuel consumption is reduced in the heating season.
● Due to the improvement of energy efficiency, it won the "white certificate" incentive.
● The return on investment was realized in less than 14 months, which proved the rapid return on investment (ROI).
The company is looking for a technology authorized buyer/manufacturer/subcontractor. Welcome to discuss.