1. Enterprise Background And Pain Point Analysis
Many traditional enterprises face many pain points in industrial equipment data collection. These enterprises often have a large amount of production equipment, but a lack of effective data collection means that equipment operating status, production data, and other information can not be obtained in a timely and accurate obtained, which in turn affects the enterprise’s production efficiency and decision-making level.
Intellectualization and informatization are a necessary process for the transformation and upgrading of enterprises, as well as a necessary means for enterprises to occupy a place in the market competition. Although facing various pains, enterprises must overcome.
Specifically, traditional industrial equipment data collection is facing the following major problems:
Backward Means Of Data Collection: Traditional data collection methods often rely on manual operation, inefficient and error-prone, unable to meet the needs of modern production.
Serious Data Silo Phenomenon: Data between different devices can not be effectively shared, resulting in the phenomenon of information silos, affecting the enterprise’s overall data analysis capabilities.
Insufficient Data Processing Ability: The enterprise lacks professional data processing and analysis team, which is unable to conduct in-depth mining and analysis of the collected data, and it is difficult to find the value behind the data.
2. The Industrial Equipment Data Collection Solution And Implementation Effect
To address the above problems, we propose an industrial equipment data collection solution based on IoT technology. By deploying sensors, IOTROUTER Passerelle Edge Computing and other devices, the solution achieves real-time monitoring and data collection and processing of the operating status of production equipment, and analyses the data through the Digital Network Nebula platform.
1. Functions of EG Edge Gateway
Edge computing gateway is a bridge that connects devices to the cloud and is mainly used to process and analyze data from different sources and send the processed data to the cloud or other devices. It has the following main functions:
Data collection and processing: edge computing gateway can collect data from various devices and sensors and process and analyze it locally. This reduces delays in data transmission and processing and improves response time.
Security protection: Les passerelles d'informatique périphérique peuvent crypter et décrypter les données localement et protéger la sécurité des appareils et des données grâce aux mécanismes de sécurité SSL/TLS.
Network Optimization: Les passerelles Edge Computing peuvent réduire la transmission sur le réseau et la consommation de bande passante en filtrant, compressant et optimisant les données afin d'améliorer les performances et l'efficacité du réseau.
Resource management: Les passerelles informatiques périphériques peuvent surveiller et gérer les appareils et les ressources locales, coordonner et optimiser l'utilisation et l'allocation des ressources, et améliorer les performances et la fiabilité du système.
2. EG Edge Computing Gateway can be applied in various fields such as:
Maison intelligente : Edge computing gateways can be used to control smart home devices, such as temperature sensors, lighting systems, door locks, etc., to improve the performance and responsiveness of smart home systems.
Industrial automation: edge computing gateways can be used to monitor and control industrial equipment and production lines, such as robots, sensors, control systems, etc., to improve productivity and safety.
Smart City: Edge computing gateways can be used to monitor and manage city facilities and resources, such as streetlights, traffic signals, trash cans, etc., to improve the efficiency and quality of city management and services.
3. After the implementation of the programme, the enterprise has achieved significant results:
The Efficiency Of Data Collection Has Been Greatly Improved: Through the automated collection method, manual intervention has been reduced, and the accuracy and efficiency of data collection have been improved.
Data Sharing And Integration: Data interoperability between different devices is realised, information silos are broken, and a more comprehensive view of data is provided for the enterprise.
Data Value Mining: Using the powerful computing capability of the Digital Network Nebula platform, the collected data are deeply mined and analysed to help enterprises find problems in the production process, optimize the production process and improve production efficiency.
3. Summary and Prospect
Through the implementation of industrial equipment data collection solutions based on Internet of Things technology, the enterprise has successfully broken through the limitations of traditional data collection methods to achieve real-time, accurate data collection and efficient processing. This not only improves the productivity of the enterprise, but also provides powerful data support for enterprise decision-making.
Looking ahead, with the continuous progress of technology and the expansion of application scenarios, industrial equipment data acquisition will play an important role in more fields. We will continue to deepen our research and optimise our solutions to provide more efficient and smarter data collection services to help enterprises achieve digital transformation and intelligent upgrading.
