Artificial intelligence can now be used by the industrial sector to reduce energy costs through optimization, monitoring and controlling energy consumption. Most industrial factories and sites are energy intensive, and over 60% have not looked at how they can become energy efficient.

Energy usage can be controlled and managed through measurable and progressive energy management processes assisted by artificial intelligence and data-mining.

We use data-mining and AI to process information, understand where energy waste comes from and determine how it can be reduced. The AI then uses that information to manage and control energy consumption and continuously collects more information. It focuses on achieving waste reduction by applying processing improvements and supply chain efficiency to meet competitive pressures and cost reduction.

• Step 1: Through data mining Maximpact identifies process and utility systems energy saving opportunities, process bottlenecks and process variability issues.
• Step 2: Through algorithms, Maximpact minimizes energy consumption by selecting the best operational set point and equipment.
• Step 3: By integrating artificial intelligence and combining it with the data that has been uncovered through data mining, the system will autonomously manage and control energy usage to maximize efficiency.

In industrial production facilities, artificial intelligence reduces energy wastage by:

• Forecasting energy demand and aligning renewable energy output accordingly. This helps to reduce the reliance on fuel usage and reduces plant emissions. In areas where factories are fuel-reliant only, AI helps to improve fuel usage and manage the consumption smartly.
• Reducing breakdowns – AI uses a combination of analytics, sensors, and operational data to forecast any possible failures of critical energy infrastructure.
• Managing power grids autonomously – AI applications are designed to efficiently handle multiple energy sources such as solar, wind and fossilfuels allowing the Energy Forecast to be applied to energy management.
• Maximizing plant outputs by identifying the optimum process set-points
• Reducing energy consumption for heating and cooling applications
• Improving unit energy efficiency of CHP plants
• Reducing plant utility costs of compressed air, nitrogen and water by optimizing performance and sequencing, and identifying maintenance issues.

Click here to find out more about energy efficiency in your industrial sectors.