Selected Industry Solutions

Industrial Internet

Integrated Cloud-edge

AIoT

TimeLyre

Industry pain points

Data Difficulties

There are many data systems and data types. Data is scattered; there are many types of industrial system protocols and databases, and it is difficult to access and aggregate data; the quality of industrial data is uneven, and there is a lack of unified data standards and management processes.

Application Difficulties

Most of the data are only used for statistics and report analysis, lack of in-process monitoring and prior prediction, and the utilization of data and analysis efficiency are low;Most production processes mainly rely on artificial experience and mechanism models, and the application of deep intelligent analysis based on industrial big data is insufficient.

Technical Difficulties

Lack of industrial big data platform and artificial intelligence deep mining tools and related technical talents, insufficient application of emerging technologies; lack of data security management and control mechanism and technology platform, the management, process, operation and other top-secret data of enterprises involved in industrial production cannot be safely circulated.

Data Difficulties

There are many data systems and data types. Data is scattered; there are many types of industrial system protocols and databases, and it is difficult to access and aggregate data; the quality of industrial data is uneven, and there is a lack of unified data standards and management processes.
Application Difficulties

Most of the data are only used for statistics and report analysis, lack of in-process monitoring and prior prediction, and the utilization of data and analysis efficiency are low;Most production processes mainly rely on artificial experience and mechanism models, and the application of deep intelligent analysis based on industrial big data is insufficient.
Technical Difficulties

Lack of industrial big data platform and artificial intelligence deep mining tools and related technical talents, insufficient application of emerging technologies; lack of data security management and control mechanism and technology platform, the management, process, operation and other top-secret data of enterprises involved in industrial production cannot be safely circulated.

The Solution of Industrial Internet

Solution Highlights

Cost-effective

Through the edge computing platform, low-cost intelligent transformation of traditional equipment can be carried out. At the same time, the time-series database TimeLyre deployed on the edge can reduce processing delay, improve response timeliness, make computing closer to the data source, and enhance the value of data;In addition, data can be preprocessed at the edge to filter low-value data and reduce the network bandwidth for data transmission from the edge to the cloud.

Device

management

The distributed time series database TimeLyre Tag has the advantage of managing the number of devices. A single node can reach one million levels, and it can expand approximately linearly. It is suitable for multiple factories, multiple production lines, and massive equipment.

Integrated

Cloud-edge

Cloud-edge time-series data storage services are coordinated, and edge-end data can be synchronized to the central end with low bandwidth, fast and senseless; the cloud-edge model is synergistic, and the cloud model can be continuously iterated to the edge.

Cross-database

Association

The distributed time series database TimeLyre can support the aggregation and correlation analysis of massive industrial time series data, and can be correlated with the distributed analytical database ArgoDB across databases to meet the query and analysis of various business scenarios.

Cost-effective

Through the edge computing platform, low-cost intelligent transformation of traditional equipment can be carried out. At the same time, the time-series database TimeLyre deployed on the edge can reduce processing delay, improve response timeliness, make computing closer to the data source, and enhance the value of data;In addition, data can be preprocessed at the edge to filter low-value data and reduce the network bandwidth for data transmission from the edge to the cloud.
Device management

The distributed time series database TimeLyre Tag has the advantage of managing the number of devices. A single node can reach one million levels, and it can expand approximately linearly. It is suitable for multiple factories, multiple production lines, and massive equipment.
Integrated Cloud-edge

Cloud-edge time-series data storage services are coordinated, and edge-end data can be synchronized to the central end with low bandwidth, fast and senseless; the cloud-edge model is synergistic, and the cloud model can be continuously iterated to the edge.
Cross-database Association

The distributed time series database TimeLyre can support the aggregation and correlation analysis of massive industrial time series data, and can be correlated with the distributed analytical database ArgoDB across databases to meet the query and analysis of various business scenarios.

Application Scenarios / Cases

Equipment Management and Predictive Maintenance
Process optimization
Factory Safety Production

Equipment Management and Predictive Maintenance

A photovoltaic new energy customer has built an industrial Internet platform of "integration of cloud and edge" based on Transwarp industrial Internet solution.The edge realizes the operation and management analysis of a single power station and the monitoring and alarming of real-time indicators of the equipment. At the same time, according to the relevant data, abnormal power generation status is found, and an operation and maintenance work order is formed to help the power station operation and maintenance personnel to achieve predictive maintenance and management;The cloud realizes the centralized control and management of indicators such as daily power generation, monthly power generation, regional power station benchmarking analysis, and key equipment statistical analysis of all power stations, helping headquarters managers to grasp the overall power generation status and key anomalies of power stations in each region.

Industrial Internet

TDH

ArgoDB

Sophon