Solution for Data Acquisition and Remote Monitoring System of Automatic Fabric Spreading Machine

Industry Background:
With the rapid advancement of technology and the continuous pursuit of production efficiency, industrial automation has become an indispensable part of the manufacturing sector.

 Against this backdrop, various automatic textile machines, including automatic fabric spreading machines, have been widely adopted, yielding tangible benefits in terms of increased production efficiency and reduced costs. However, alongside these productivity gains, new challenges have emerged in effectively managing and maintaining equipment to ensure stable production operations.

Demand Analysis:

1. The proliferation of industrial automation has created a demand for efficient management, necessitating digitalized management solutions.
2. Key equipment such as fabric spreading machines requires real-time monitoring to ensure continuous and effective operation, necessitating the ability to monitor device operational status.
3. The traditional manual operation and maintenance model is costly and slow to respond, failing to meet the requirements of modern production lines, demanding cost reduction and efficiency enhancement.

Solution:
To address these challenges, WideIOT has introduced an advanced Internet of Things (IoT) technology and big data analytics approach, launching a data acquisition and remote monitoring system for automatic fabric spreading machines.

 This system utilizes an industrial intelligent gateway to collect operational status information from the fabric spreading machine and transmits this data (via 5G/4G/WIFI/Ethernet) to a cloud platform or upper computer for instant analysis. It enables functions such as abnormality early warning, fault diagnosis, operation and maintenance management, visual display, and data analysis.

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System Functions

1. Real-time Monitoring: Continuously monitors the working parameters and operational status of the fabric spreading machine.

2. Fault Early Warning: Utilizes rule-based algorithms to identify potential issues and issue early warnings in advance.

3. Data Analysis: Collects vast amounts of operational data to support deep learning and artificial intelligence-assisted optimization.

4. Remote Maintenance: Allows technicians to perform remote programming, debugging, and program uploading/downloading operations.

5. Maintenance Management: Formulates precise operation and maintenance plans based on machine conditions and enables real-time query and management.

6. Visual Display: Establishes a personalized and aesthetically pleasing data dashboard for quick comprehension of comprehensive information.