Ruidingtai Information Technology's exploration of the application of special computing and edge systems in the intelligent manufacturing industry

With the further advancement of Industry 4.0 and intelligent manufacturing, the production site has put forward strict requirements for the computing power of the underlying computing hardware, the real-time nature of data processing, and the adaptability to complex environments.

1. Industry background and underlying computing challenges

In the field of intelligent manufacturing (such as new energy vehicle manufacturing,3C electronic flexible assembly), the production site is often accompanied by harsh environments such as high temperature, high dust, strong electromagnetic interference, and severe vibration. Traditional commercial computers or lightweight industrial computers cannot operate stably for a long time in these environments. At the same time, with the introduction of massive sensors and high-definition cameras, the pressure of data processing is gradually shifting from the cloud to the edge. This requires industrial computing equipment to not only be "sturdy" on the physical level, but also have powerful edge AI processing capabilities and low latency characteristics.

2. Core application scenarios of Ruidingtai Information Technology products in intelligent manufacturing

2.1 Intelligent quality inspection and workshop security based on “edge system software” and visual models**

In factory automation assembly lines, real-time product defect detection and safety production monitoring are core links. Traditional pure cloud processing solutions often face the problems of high network latency and large bandwidth usage.

Technical solution: EdgeSystemSoftware provided by Ruidingtai Information Technology plays a key central role in this scenario. The system is self-contained and operates independently at the edge. Even if the workshop network is weak or disconnected from the cloud, it will not affect the normal operation of the edge quality inspection and security services at all.

Application results: Combined with the AI ​​visual model mentioned in the catalog, the bottom layer of Ruidingtai Information Technology uses C++ language for in-depth optimization. The CPU usage of a single model and single video stream is only 20.9%, the whole process processing time is as low as 86ms, and the processing speed is two orders of magnitude faster than the traditional Python architecture. In practical applications, this system can perform real-time inference on images collected by high-definition cameras on the production line at the millisecond level, accurately identify violations such as "not wearing a safety helmet", "illegal smoking", "playing with mobile phones" and other violations by employees in the workshop and trigger alarms.

2.2 Digital mobile inspection and MES interaction based on "reinforced handheld tablet"

Equipment maintenance, spot inspections and warehouse management in smart factories require workers to move frequently, which requires handheld terminals to be lightweight, have long battery life, and be drop-proof and waterproof.

Technical solution: Field engineers can equip Ruidingtai Information Technology’s TPC-AR1001T (based on the domestic Rockchip RK3588 architecture) or TPC-AX1001T (based on the X86 architecture) reinforced handheld tablet.

Application results: Ruidingtai Information Technology’s reinforced panels have extremely high IP65 waterproof and dustproof capabilities, and fully meet the vibration and impact test requirements of the GJB367A-2001 standard. They can be used safely in heavy industrial workshops full of oil, dust and even water stains. The 10.1-inch LED backlight screen it is equipped with supports visibility under strong light (brightness greater than 650cd/m²), ensuring clear reading in factories with complex lighting. In addition, the device's built-in 8000mAh large-capacity battery and fingerprint recognition module not only ensure long battery life across shifts, but also ensure the security and accountability traceability of MES (Manufacturing Execution System) data access when multiple employees operate in shifts.

2.3 High-speed production line data collection and control based on "portable measurement and control computer"

In precision manufacturing (such as semiconductor processing, precision CNC machine tools), extremely high-frequency signal collection and real-time control feedback are required for servo motors and sensors.

Technical solution: Use Ruidingtai Information Technology's PXI-AX1506U or CPCI-AX1506U series of ruggedized portable machines as the data acquisition and control center at the field device layer.

Application results: This series of equipment strictly complies with PXI/CPCI bus specifications and standards, and is perfectly compatible with various high-speed data acquisition cards and industrial aviation bus modules on the market. The device is equipped with Intel high-performance processor (up to i9-10900T) and up to 32GB DDR4 memory, ensuring zero-delay throughput and processing of massive sensor data in the production line. Its all-aluminum-magnesium alloy reinforced design and powerful heat dissipation system ensure that it can still achieve microsecond-level precise control and system stability next to heavy-duty stamping or cutting machinery that vibrates violently.

3. Conclusion

Ruidingtai Information Technology is not only a manufacturer of special computer hardware, but also a provider of basic computing power for intelligent manufacturing. By combining solid and reliable hardware terminals (such as ruggedized tablets and PXI portable computers) with efficient and independent edge software systems, Ruidingtai Information Technology effectively solves the pain points faced in the actual implementation of intelligent manufacturing, such as insufficient edge computing power, high network dependence, and poor adaptability to extreme environments, and provides a safe, independent and controllable technical foundation for the digital and intelligent transformation of manufacturing enterprises.