A Digital Twin is an innovative method that represents a virtual replica of a real-world system or grid, used to simulate and manage operations and created using advanced virtualization and modeling technologies.
about the product
about the product
A Digital Twin is a digital representation of a real-world object or system. It is an evolving digital profile of the historical and current behavior of a physical object or process.
3 components
FACEPLATE includes the kernel, development environment, and execution environment
has all the advantages of non-SQL DBMS and is optimized for storing large amounts of data and organizing optimal access to them
development environment, a complete set of software tools for human-machine interface design, control algorithm development, archive configuration, reports, warning systems and other functions
execution environment, real-time automated control system
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information
Faceplate Platform
Monitoring, diagnostics, and forecasting
Maintenance services
Optimization of resources and security services
Lifecycle Management
strengths
Faceplate features
1. Object modeling
2. Real-time monitoring
3. Forecasting and data analysis
4. Equipment control
5. Decision-making
6. Reducing costs and resource intensity
7. Maintenance planning
8. Interaction with other systems
9. Virtual testing and scenarios
10. Optimization of energy consumption
11. Network security
12. Automation of solutions
1. Object modeling
-constant monitoring of object data and parameters
-automatic updating of the digital twin as the state of the object changes
2. Real-time monitoring
-constant monitoring of object data and parameters
-automatic updating of the digital twin as the state of the object changes
3. Forecasting and data analysis
-analyzing historical data to identify trends and patterns
-predicting future states of an object's behavior based on the collected data
4. Equipment control
-remote control and monitoring of equipment condition
-rapid response to failures
-automatic optimization of mechanisms
5. Decision-making
-digital twin data analysis for operational decision-making
-minimizing risks
-improving the efficiency of business processes
6. Reducing costs and resource intensity
-optimizing resource usage based on digital twin data
-reduction of energy and materials costs
-reduced maintenance costs
7. Maintenance planning
-maintenance and repair history
-maintenance and prevention plans
-reports and data on technical condition
8. Interaction with other systems
-integration of the digital twin with other technological systems
-data exchange to create a unified information environment
9. Virtual testing and scenarios
-developing virtual scenarios for assessing potential changes in actual systems
-examining diverse conditions and situations to proactively address potential issues
-exploring various conditions and scenarios to enhance system optimization
10. Optimization of energy consumption
-real-time monitoring and analysis of energy consumption data
-development and implementation of strategies to reduce energy consumption
-improvement of energy efficiency
11. Network security
-ensuring the safeguarding and confidentiality of production information systems
-monitoring for potential threats and preventing cyber attacks
-conducting security audits and updating security measures
12. Automation of solutions
-using machine learning algorithms for automatic decision-making
-responding to changes in real time
-making optimal decisions without human intervention
1. Моделирование объектов
2. Мониторинг в реальном времени
3. Прогнозирование и анализ данных
4. Управление оборудованием
5. Принятие обоснованных решений
6. Снижение затрат и ресурсоемкости
7. Планирование технического обслуживания
8. Взаимодействие с другими системами
9. Виртуальное тестирование и сценарии
10. Оптимизация энергопотребления
11. Сетевая безопасность
12. Автоматизация решений
1. Object modeling
-constant monitoring of object data and parameters
-automatic updating of the digital twin as the state of the object changes
2. Real-time monitoring
-constant monitoring of object data and parameters
-automatic updating of the digital twin as the state of the object changes
3. Forecasting and data analysis
-analyzing historical data to identify trends and patterns
-predicting future states of an object's behavior based on the collected data
4. Equipment control
-remote control and monitoring of equipment condition
-rapid response to failures
-automatic optimization of mechanisms
5. Decision-making
-digital twin data analysis for operational decision-making
-minimizing risks
-improving the efficiency of business processes
6. Reducing costs and resource intensity
-optimizing resource usage based on digital twin data
-reduction of energy and materials costs
-reduced maintenance costs
7. Maintenance planning
-maintenance and repair history
-maintenance and prevention plans
-reports and data on technical condition
8. Interaction with other systems
-integration of the digital twin with other technological systems
-data exchange to create a unified information environment
9. Virtual testing and scenarios
-developing virtual scenarios for assessing potential changes in actual systems
-examining diverse conditions and situations to proactively address potential issues
-exploring various conditions and scenarios to enhance system optimization
10. Optimization of energy consumption
-real-time monitoring and analysis of energy consumption data
-development and implementation of strategies to reduce energy consumption
-improvement of energy efficiency
11. Network security
-ensuring the safeguarding and confidentiality of production information systems
-monitoring for potential threats and preventing cyber attacks
-conducting security audits and updating security measures
12. Automation of solutions
-using machine learning algorithms for automatic decision-making
-responding to changes in real time
-making optimal decisions without human intervention
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more detailed
1
of historical data, allows troubleshooting, and real-time root cause analysis
2
of reasonable objectives in light of the facility's existing operational state
3
to improve maintenance forecasts, equipment operation schedules, and energy consumption tuning
4
to proactively reduce operational risks and plan actions in emergency situations
5
training of personnel in a virtual environment, which reduces the risks of emergencies and increases overall safety
6
the efficient utilization
of material and human resources to achieve cost savings and enhance productivity
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