advanced ai solution to predict industrial equipment downtime
A big data analysis and digital modeling system that uses machine learning to predict the technological situations, and also includes a recommendation system to support a decision-making.
It is designed to automate the collection, storage, processing and analysis of data for AI solutions to automate and simplify task setting, create and evaluate machine learning models and implement models into workflows.
DATASKAI for a tube-rolling production
Take a look on our example system usage in tube-rolling production. Predictions, alerts, dashboards.
>2000
number of signals simultaneously processed by the DATASKAI system
advanced ai solution to predict industrial equipment downtime
A big data analysis and digital modeling system that uses machine learning to predict the technological situations, and also includes a recommendation system to support a decision-making.
It is designed to automate the collection, storage, processing and analysis of data for AI solutions to automate and simplify task setting, create and evaluate machine learning models and implement models into workflows.
DATASKAI for a tube-rolling production
Take a look on our example system usage in tube-rolling production. Predictions, alerts, dashboards.
50+
AI Detectors
advanced ai solution to predict industrial equipment downtime
A big data analysis and digital modeling system that uses machine learning to predict the technological situations, and also includes a recommendation system to support a decision-making.
It is designed to automate the collection, storage, processing and analysis of data for AI solutions to automate and simplify task setting, create and evaluate machine learning models and implement models into workflows.
DATASKAI for a tube-rolling production
Take a look on our example system usage in tube-rolling production. Predictions, alerts, dashboards.
3
months until the system is fully equipped
advanced ai solution to predict industrial equipment downtime
A big data analysis and digital modeling system that uses machine learning to predict the technological situations, and also includes a recommendation system to support a decision-making.
It is designed to automate the collection, storage, processing and analysis of data for AI solutions to automate and simplify task setting, create and evaluate machine learning models and implement models into workflows.
DATASKAI for a tube-rolling production
Take a look on our example system usage in tube-rolling production. Predictions, alerts, dashboards.
100%
autonomous detection system
Control of technological processes using AI, prediction and prevention of equipment failures in industrial plants by detecting anomalies in the joint signals and searching for dependencies in data from measuring sensors.
dataskai Solving tasks
and chances
DATASKAI contains a built-in data pipeline that allows you to connect to time series of up to 2000 signals simultaneously, identify characteristic features of signals (manually and automatically) build models for detecting signal anomalies (with help of a data specialist), build detectors, and include trained models in real-time workflows, also contains a configurable user interface without programming.
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Integration of neuro-network models to obtain solutions and recommendations
Leverage advanced neural network models for generating actionable insights and recommendations, optimizing process efficiency and effectiveness.
Integration with Automated Control System (ACS)
This feature allows DATASKAI to integrate smoothly with Automated Control Systems, helping in efficient management and automation of industrial processes.
Recommendation interface for monitoring and decision-making
Access a user-friendly interface designed to assist in monitoring operations and making informed decisions, enhancing operational efficiency and safety.
Neuro-network processing of real-time data
Implement neural network capabilities to process real-time data streams, providing immediate anomaly detection and decision support for critical operations.
Digital production modeling
Use DATASKAI to create accurate digital models of production processes, enabling simulations and optimizations for improved productivity
Marking up data and providing its access
Easily annotate and organize your data, making it accessible for analysis and reporting. This feature enhances data categorization and retrieval processes.
Connecting different data sources
DATASKAI enables seamless connectivity with a variety of data sources, including TCP/UDP IP protocols, DMS, and SCADA systems. This ensures comprehensive data integration for effective monitoring and analysis
Possibility to process retro-data
Analyze historical data to identify patterns and trends, allowing for retrospective insights and long-term planning.
Data collection and storage
Collect and store vast amounts of data from multiple sources efficiently. DATASKAI provides secure, scalable storage solutions for managing real-time and historical data
Integration of neuro-network models to obtain solutions and recommendations
Leverage advanced neural network models for generating actionable insights and recommendations, optimizing process efficiency and effectiveness.
Integration with Automated Control System (ACS)
This feature allows DATASKAI to integrate smoothly with Automated Control Systems, helping in efficient management and automation of industrial processes.
Recommendation interface for monitoring and decision-making
Access a user-friendly interface designed to assist in monitoring operations and making informed decisions, enhancing operational efficiency and safety.
Neuro-network processing of real-time data
Implement neural network capabilities to process real-time data streams, providing immediate anomaly detection and decision support for critical operations.
Digital production modeling
Use DATASKAI to create accurate digital models of production processes, enabling simulations and optimizations for improved productivity
Marking up data and providing its access
Easily annotate and organize your data, making it accessible for analysis and reporting. This feature enhances data categorization and retrieval processes.
Connecting different data sources
DATASKAI enables seamless connectivity with a variety of data sources, including TCP/UDP IP protocols, DMS, and SCADA systems. This ensures comprehensive data integration for effective monitoring and analysis
Possibility to process retro-data
Analyze historical data to identify patterns and trends, allowing for retrospective insights and long-term planning.
Data collection and storage
Collect and store vast amounts of data from multiple sources efficiently. DATASKAI provides secure, scalable storage solutions for managing real-time and historical data
system architecture
equipment downtime prediction
Integration of neuro-network models to obtain solutions and recommendations
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Training based on the data of identified anomalies in work (downtime)
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Organization of the models (detector) operation in real time mode
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Prediction of equipment downtime
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Integration and data selection from the observed equipment
Connect and select data from monitored equipment to gather essential information for analysis and process monitoring
Search for significant features
Automatically identify key characteristics and features in the data that impact equipment operation and processes
Building machine learning models
Develop machine learning models designed for specific industrial tasks to enable effective analysis and prediction
Training based on the data of identified anomalies in work (downtime)
Train models using data from identified anomalies and downtimes to enhance prediction accuracy and reliability
Choosing the architecture of machine learning models
Select the optimal architecture for machine learning models, tailored to the specific data and tasks for best results
Organization of the models (detector) operation in real-time mode
Configure models to operate in real-time for immediate detection and response to anomalies
Prediction of equipment downtime
Desig create
Predict equipment downtimes to prevent failures and improve production efficiency through timely preventive measures
DATASKAI example usage for a tube-rolling production
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Location
Lesnaya street, 5, Moscow, Russia, 125047
E-Mail
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The framework belongs to the class «Big Data Processing Tools» of the section «Data Array Processing and Visualization Tools» of the Classifier of Programs for Electronic Computers and Databases, approved by order of the Ministry of Digital Development, Communications and Mass Media of the Russian Federation dated September 22, 2020 No. 486.
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A big data analysis and digital modeling system
