Platform360 Energy Monitoring

Industry leaders take their steps in energy with a holistic approach. The value added by energy data alone increases exponentially when combined with operational data.

What is Energy Monitoring?

Energy is an important cost item in the overall operational costs of companies. Companies that accurately monitor their energy consumption can reduce unnecessary consumption, report product-based energy costs more accurately, and increase the reliability of their systems by monitoring anomalies.

Industry leaders take their steps in energy with a holistic approach. The value added by energy data alone increases exponentially when combined with operational data. The insight created when energy data is combined with operational data, can make processes more energy efficient.

Monitoring of historical energy consumption data also provides value for estimating future energy use and therefore of the cost. Measurement data, backed up with operational and environmental data, enables the estimation and optimization of future consumption and in turn costs by employing analytics models

Why Energy Monitoring?

Platform360 Energy Monitoring and Management provide solution in 5 layers;

Data collection: Energy consumption data is collected with hardware suited for the needs. Energy data is collected through an energy meter, energy analyzer and even through integration with electric vehicle charging stations.
Data Processing: With real-time processing of data, alarm/events are instantly detected and action is taken.
User-defined interfaces: Users can visualize the data they want to see on dashboards they design. Details of the data can be adjusted based on the time/shift/location of the facility or comparative examinations can be done, if needed.
Shared Service Layer: With Platform360 internet of things platform, data can be interpreted by matching with operational systems.
Advanced Analytics: Prospective energy consumption can be predicted with advanced analytics capabilities.

Features

01Monitors energy data

• Variables such as voltage, frequency, reactive energy data can be displayed real time.
• Breakdown of energy consumption can be monitored by area, line, and station across the production.
• Breakdown of energy consumption by departments and divisions can be monitored.
• Source and details of the energy used (grid, generator, battery) are monitored.
Compatible with different brand and model meters and analyzers.
• No hardware dependency, easy integration of new hardware with ready SDK and API support.

02Customizable reports to suit your business

• Users can customize the data interfaces they want to see with the self-service reporting capabilities.
• Operational costs are reported more accurately with actual energy data.
• Energy consumption trend analyses are created.

03Predicts the future

• Combined with operational data, energy consumption can be forecasted with high accuracy.
• Data is provided to predictive maintenance systems based on anomalies in energy consumption.

04Analyzes the data

• Users can set up rule engines to trigger alarms or initiate actions based on the energy consumption.
• Automated work orders can be opened for maintenance teams in risky areas with anomalies in energy consumption.
• Correlation analysis of energy consumption can be carried out across manufacturing operations.

Benefits

Efficiency

    Energy prices vary considerably and continue to take an increasingly growing share in operational costs.
    Monitoring and analysis of energy consumption and optimization of energy utilization.
    Identification of hardware which replacement is suggested due to anticipated malfunction and wearing out.

Accountability

    Monitoring energy consumption by departments enables costs to be correctly included in department budgets.
    A single, end-to-end image of energy utilization can be generated.

Reliability

    Detection of anomalies in energy consumption and necessary data sets the basis for predictive maintenance.
    Malfunctions that will cause unplanned operational disruptions are minimized by using the system in combination with predictive maintenance.

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