Energy Management

Forecast & optimize energy consumption to reduce cost and wastage.

Industry Challenges

Manufacturing processes consume a significant amount of energy, of which approximately 30% is wasted every year and this accounts for a substantial portion of production costs. There can be several factors responsible for this wastage such as outdated equipment, inefficient lighting, leaky air compressors, and inadequately utilized heating/cooling. Energy wastage coupled with fluctuations in demand negatively impacts an organization’s bottom-line and sustainability goals. Can implementing AI in energy management prove effective here? Read how AI-powered Energy Management Services Program helps in improving energy efficiency.

DT4o Solutions

To address these challenges, DT4o offers solutions for better energy management solutions that offer advanced connectivity of devices, services, and systems to gain business insights with analytics.

  • Forecast production and demand to predict spikes and avoid idle time

  • Streamline value chain processes to reduce costs

  • Monitor, predict and reduce carbon emissions by providing detailed insights into every aspect of the production process and thereby meet sustainability goals

  • Real-time optimizers to monitor efficiency of assets and equipment to improve system dependability

Key Challenges & DT4o Energy Management Solutions

Solution

As an energy management company, our AI-driven data provides real-time insights and recommendations to identify the best approach to minimize costs and decrease carbon emissions

Solution

Reduce complex mesh of data into user friendly simple metrics to allow better analysis and resolve problems as they arise.

Solution

Machine learning enabled automation of measuring KPIs to accurately track sustainability and cost reduction goals and enable effective reporting thus improving reliability.

Solution

Real-time insights to track condition of assets and equipment to detect causes for idle time

Core Capabilities

Deploying AI-derived data to reduce energy use and improve productivity and yield through a more proactive and predictive approach by a leader among AI energy companies to enable better decision making.

AI-Driven Real-time Insights to Improve Operational Efficiency

AI-Driven Real-time Insights to Improve Operational Efficiency

  • AI can identify main factors responsible for higher carbon emissions and costs
  • Predictive analytics ensures energy spikes are managed effectively in order to reduce costs
  • Prescriptive measures based on AI-driven data, such as those provided by an energy management company like DT4o, enable better energy conservation
  • Monitor important KPIs such as energy, water, waste, etc., in real-time to improve efficiency
  • Allows the enterprise’s processes to be benchmarked against peers after a successful implementation of energy management services

Business Benefits