Solution

Smart energy meters are connected to various individual equipment to get accurate electrical parameter data. These are connected to an Edge IoT device, which captures the information from the meters either wirelessly (WiFi, 4G etc) or through wired protocols (Modbus, Profibus etc). Basic analysis and alerting at the Edge. Deeper analysis in a central cloud historian. Data is fed into a machine learning and prediction engine.

Places

This system is optimal to deploy for any kind of manufacturing setup, and can be deployed across the factory shop floor. The hardware is cost effective and easily available, while the software is modular and easily scalable. This enables easy deployments across geographies.

Need

Electricity consumption is a major expense in any factory. The system provides SMS Alerts for proactive action and key dashboards to generate insights. Pre-Built machine learning algorithms have been developed to provide insights of future operation. Some examples of use cases are; Energy forecasting, Current and Power based condition monitoring, Root cause analysis, Max Demand Alerting, Equipment / Group of Equipment comparison across plants, Equipment / Group of equipment comparison over time, comparison of consumption across products and many more.

Impact

In general, the impact of implementing this system, along with the necessary actions would lead to anywhere between 2% - 8% energy savings, with certain factories achieving close to 15% reduction. Additional outcomes would include a 8% - 10% reduction in man hours (to engage in more productive and high value tasks) and a 2% - 5% improvement in equipment reliability.