Main uses of Smart RDM in heating and power generation
- Fault detection
- Visualization of the operating status of equipment: units, boilers, turbines, etc.
- Equipment operation diagnostics
- Monitoring of production plans
- Automatic reporting
Heat demand forecast
- A prediction model using a statistical algorithm using historical data.
- Prediction model calculated in accordance with locally applicable regulations on shaping and calculating tariffs and settlements for heat supply.
- Prediction model using machine learning algorithms.
Optimal configuration of production units (ERO)
- Determination of optimal configuration of generating units based on efficiency and availability characteristics taking into account start-up/shutdown costs within a 72-hour horizon
Optimal production and delivery parameters
- Determination of system water parameters based on the control table
- Comparison of parameters with actual values, deviation analysis
What are the benefits
of Smart RDM
Support for the detection of failures and overruns
Automatic reporting to authorities
Improved repair and maintenance planning
Key real-time infrastructure status information
Reduction of CO2 emissions
Reduce repair costs
Smart RDM - standard version
Production Optimization in Five Steps
01. Data Integration
The first step is to integrate all key real-time production data.
Effect
Create a single source of truth for business systems securely separated from critical infrastructure.
02. Building context
The second step is to map the technical infrastructure and production processes in a digital model. Appropriate codification, delivered during implementation, will enable monitoring and analysis of the production line status. Each monitored element of the machine will have its unique code in the system combined with corresponding data from measuring devices.
Effect
Ability to reliably compare infrastructure elements, analyze them, and quickly add new elements to the model, such as a branch, block, sensor, or business indicator.
03.Visualization and monitoring
The third step is the digital mapping of processes on interactive synoptic masks. For each element of the technical infrastructure of the unit a digital schematic is prepared so that operators have a real-time overview of the situation
Effect
Overview of current and historical technical parameters of machines. Quick reaction to events.
04. Alarms and notifications
The system allows you to configure alarm thresholds and anomaly notifications for irregularities, schedule overruns, or performance. Events are integrated with notifications sent to defined users. The system operator has the ability to redirect events to the appropriate service along with the necessary information about the event and its location
Effect
Automation and reduction of failure handling time.
05. Analysis and reporting
The system enables efficient and automatic reporting. Industry report templates are prepared as part of the standard.
Effect
Present results to managers and quickly handle legally required reports.
Smart RDM - extended version
Energy Production - Advanced Industry Algorithms
Once the basic needs of equipment condition monitoring and reporting are met with Smart RDM, we will meet the new challenges of production optimization.
The business environment will push for continuity of energy supply, reduced downtime and higher equipment efficiency as well as control and reduction of CO2 emissions. In the Big Data module, we use specialized computing algorithms to clean and populate data, detect anomalies to avoid failures, forecast production, plan maintenance and optimize blocks.
