ARMxy BL440 + NPU AI visual inspection for smart manufacturing: sub-millimeter precision, 120pcs/min speed, cuts 60% labor cost & 30-50% defects. Real-time, traceable, multi-scenario.
Case Details
In the intelligent manufacturing industry, product quality inspection is a critical link affecting production efficiency, brand reputation, and customer satisfaction. Traditional quality inspection methods face core challenges such as high manual error rates, low detection efficiency, inconsistent standards, and difficulty in data tracing. This solution, based on the
ARMxy BL440 industrial-grade embedded computer and its built-in 6TOPS high-performance NPU, constructs an AI visual inspection system integrating real-time image processing, intelligent algorithm analysis, multi-protocol data fusion, and full-process traceability. By adopting a deep learning-based multi-feature recognition algorithm, it achieves sub-millimeter-level detection accuracy and millisecond-level response speed. Combined with the three core software tools—BLIoTLink, BLRAT, and Qt visual development framework—the solution ultimately reduces manual inspection costs by over 60%, lowers product defect rates by 30%-50%, and realizes full-process digital traceability of product quality.
- Manual Inspection Limitations: Fatigue-induced missed inspections and false detections, with error rates exceeding 5% for fine-grained products.
- Inconsistent Standards: Subjective judgment differences among inspectors lead to uneven quality control levels.
- Data Isolation: Disconnected detection data from production systems, making it impossible to trace defect causes and optimize processes.
- Poor Flexibility: Traditional detection equipment is difficult to adapt to rapid product model changes, resulting in high transformation costs.
The ARMxy BL440 + NPU combination delivers four core values for intelligent visual inspection:
- High-Performance AI Computing: Built-in 6TOPS NPU supports INT4/INT8/INT16 multi-precision computing, enabling real-time inference of complex deep learning models.
- Hard Real-Time Response: Equipped with Linux-RT real-time kernel and EtherCAT industrial Ethernet, ensuring millisecond-level synchronization between image acquisition and detection results.
- Multi-Scenario Adaptability: Supports 4K@60fps high-definition image input and multi-model rapid switching, adapting to inspection needs of different products and processes.
- Full-Lifecycle Management: Integrates data collection, analysis, traceability, and remote maintenance, forming a closed-loop of quality control.
This solution adopts a "cloud-edge-device" three-tier collaborative architecture:
- Device Layer: High-definition AI cameras, laser sensors, and EtherCAT-enabled actuators collect product image and dimensional data in real time.
- Edge Layer: ARMxy BL440 serves as the core controller, undertaking AI model inference, real-time data processing, and control command issuance.
- Cloud Layer: Receives and stores detection data from edge devices, supports statistical analysis, defect tracing, and model iterative optimization.
- AI Visual Detection Algorithm: Integrates target detection, image segmentation, and dimensional measurement models, achieving simultaneous recognition of surface defects, assembly deviations, and size tolerances.
- Real-Time Data Transmission: Based on EtherCAT and MQTT protocols, realizing low-latency transmission of detection data and production system interconnection.
- Multi-Source Data Fusion: Fusing image data with sensor data (temperature, pressure) to improve detection accuracy and reduce false alarm rates.
- Remote Management Platform: Through BLRAT remote access tool, realizing remote debugging of detection parameters, model updates, and equipment maintenance.
- Main Controller: ARMxy BL442B (2×1000M + 1×100M Ethernet ports, supports HDMI2.1 display, 2 Y-board slots)
- Core Board: SOM442 (RK3576, 4×Cortex-A72 + 4×Cortex-A53, 8GB LPDDR4X, 64GB eMMC, 6TOPS NPU)
- Peripheral Configuration: 4K AI industrial camera (2pcs), EtherCAT slave station module, laser displacement sensor, touch screen display, alarm actuator
- Expansion Module: Y37 IEPE measurement module (for vibration data collection), Y63 RS485 module (for connecting production line PLC)
- Ultra-High Precision: Sub-millimeter-level detection accuracy (±0.01mm), covering micro-defects that are difficult to identify manually.
- Efficient and Stable: 24/7 continuous operation, detection speed up to 120 pieces/minute, avoiding human fatigue impacts.
- Digital Traceability: Each product's detection data (images, results, time) is recorded and uploaded to the cloud, supporting full-process traceability.
- Low-Cost Upgrade: Compatible with existing production lines, supporting rapid switching of detection models for new products without major hardware modifications.
This solution is suitable for:
- Electronic component inspection (chip pin defects, PCB solder joint detection)
- Auto parts inspection (casting surface defects, assembly gap measurement)
- 3C product inspection (screen scratches, battery assembly deviation)
- Medical device component inspection (injection molding part burrs, precision fitting detection)
- New energy battery inspection (cell surface defects, tab welding quality)
The
ARMxy BL440 + NPU AI visual inspection system addresses the core pain points of traditional quality inspection through three-dimensional innovation: hardware computing power, algorithm intelligence, and software ecosystem integration. The solution not only achieves high-precision, real-time, and automated product inspection but also provides data support for production process optimization through full-process traceability. It is an important technical support for manufacturing enterprises to achieve quality upgrading, cost reduction, and efficiency improvement, and a key path to build smart factories.
