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 job sites are energy intensive, and over 60% have not explored how they can become more energy efficient.
Energy use can be controlled and managed through measurable and progressive energy management processes assisted by artificial intelligence and data mining.
We at Maximpact 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 energy saving opportunities in process and utility systems, pinpoints process bottlenecks and diagnoses 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 waste by:
- Forecasting energy demand and aligning renewable energy output accordingly: This helps to reduce reliance on fuel use 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 fossil fuels, allowing the energy forecast to be applied to energy management.
- Maximizing plant outputs by identifying the optimal process set-points
- Reducing energy consumption for heating and cooling applications
- Improving unit energy efficiency of combined heat and power plants, or CHP plants, also called cogeneration plants
- Reducing plant costs for compressed air, nitrogen and water by optimizing performance and sequencing, and by identifying maintenance issues.
Click here to find out more about energy efficiency in your industrial sector.