Improve your overall equipment effectiveness (OEE),
reduce the cost per unit
with real-time control

The weekly, monthly, quarterly and a half-yearly specific performance indicators of oil pumping units, pumps can be displayed;
Number of start-ups and shut-downs, operating hours for each type of equipment on a time range;
Costs of electricity and other resources;
Predictive diagnostics, analysis of key parameters to identify deviations from nominal values;
Data collecting, processing and analyzing brings great opportunities to improve the efficiency of the enterprise;

Improving production efficiency by increasing productivity and quality of products, reducing energy consumption;
Increasing overall equipment effectiveness, reduction of defect and food safety risks, reduction of energy costs per unit of production;
Determine the total number of produced units, water and electricity consumption, defect rate. Provide operational active data and historical technological data regarding the status of the technological process;
Provide manufacturing performance indicators for the selected period of time to the dispatching and administrative personnel of the plant;
Create and calculate KPI of the dependency on electricity consumption and production output data;

Continuous monitoring of events, conditions, and assessing the efficiency the production;
Equipment’s KPI: during each shift is recorded the efficiency of the equipment, the causes of downtime. Loss analysis in a manufacturing plant, the number of defective and quality products with the definition of the defect cause. Analysis of the effectiveness of staff by each shift;
Registration and accounting of manufactured products at the enterprise;
Collected information structured in real-time dashboards and visualizations which keep your team and management informed;

Mining and steel companies only use a fraction of the data they collect;
To comply with strict environmental regulations, an artificial intelligence system can be used to reduce the negative impact of harmful processes;
KPI performance calculations for equipment operation. Equipment operation anomaly detection through time series analysis;
Operational display of various technological processes such as crushing, transportation, enrichment, pyro or hydrometallurgy. With obtained data technologists can analyze and adjust the process when calculating material flows;

Analytics at the generation stage, combined with an understanding of the demand for energy produced, allows you to plan the optimal production of electricity;
The platform can monitor the status of equipment and send real-time critical alerts about faults, accidents or anomalies;
Predictive maintenance provides significant economic benefits, and also extends the life of the equipment;
Solving the problem of optimizing transportation time and reducing transportation costs;

The IoT enables renewable energy companies to keep track of their physical assets remotely, and in real time, by installing a fleet of connected sensors at their facilities. This functionality is crucial for identifying maintenance issues, anticipating potentially harmful environmental conditions and monitoring ongoing performance.

Reliable monitoring systems and networking infrastructure protect against unplanned downtime. IoT sensors are capable of collecting and transmitting a massive amount of performance and environmental data remotely, which is helping organizations make evidence-based decisions when outages occur.

Advanced functionality can help improve the efficiency of renewable resources and make them easier to manage. For example, an IoT sensor installed on a solar panel would be able to detect the most favorable conditions for energy production. When fed into an automated control system, this data could help the system reorient itself to maximize outputs without any human intervention. The same is true for coastal wind turbines — AI could alter the direction these turbines are spinning in to capitalize on sudden changes in local wind patterns. When leveraged effectively, IoT and automation can improve power output, reduce operating costs related to unplanned downtime and equipment maintenance and increase the reliability of green energy systems.

Analyzing data on green power usage is also crucial for tracking the adoption of these systems in a national context.