Low Power Consumption & High Efficiency
ARM processors deliver high performance while significantly reducing energy consumption, making them ideal for 24/7 industrial operations. This minimizes cooling requirements and energy costs.
Compact & Rugged Design
Fanless and compact form factors adapt to space-constrained workshop environments, with wide-temperature operation (-40°C to 85°C), suitable for harsh conditions.
Rich Interface Support
Industrial interfaces such as RS-485/232, CAN bus, Gigabit Ethernet, and GPIO, compatible with protocols like Modbus, MQTT, enable direct connections to PLCs, sensors, and IoT devices.
Edge Computing Capabilities
Models with integrated AI accelerators (e.g., NPUs) can perform localized tasks like machine vision and anomaly detection, reducing cloud dependency and improving response times.
Cross-Platform Compatibility
HTML5-based architecture supports seamless operation on ARM/Linux or Windows systems, providing a unified web-based interface accessible via mobile devices.
Dynamic Data Visualization
Drag-and-drop editors enable rapid creation of 3D factory models, integrating real-time data streams (e.g., temperature curves, OEE dashboards) with multilingual support and alarm management.
Direct Industrial Protocol Integration
Native support for OPC UA, MQTT, and S7 communication allows direct interaction with Siemens, ABB, and other PLCs without middleware.
Cloud Collaboration
Built-in connectors for AWS IoT/Azure IoT Hub enable device-to-cloud data transfer, facilitating big data analysis and predictive maintenance modeling with time-series databases.
ARMxy SBC collect real-time motion control data via EtherCAT. ATVISE generates a digital twin of the production line, dynamically displaying cycle times, yield rates, and equipment status, triggering ANDON alerts during anomalies.
Example: In automotive assembly lines, vibration sensor data predicts robotic arm bearing lifespan, triggering maintenance orders two weeks in advance.
ATVISE consolidates energy meter data into dashboards. ARM edge nodes run algorithms to identify peak usage patterns for high-energy devices (e.g., compressors), automatically adjusting operations to reduce energy consumption by 15%.
Technical Detail: ARM GPIO controls smart relays to implement time-based power strategies.
ARM devices run TensorFlow Lite models to analyze motor current harmonics. ATVISE visualizes equipment health indices, triggering work orders when anomalies (e.g., insulation degradation) are detected.
Data Flow: Vibration sensors → ARM edge FFT analysis → feature extraction → ATVISE visualization → threshold-based alerts.
ATVISE synchronizes ERP order data, while ARM controllers dynamically adjust AGV routes and machining center parameters for small-batch, multi-variant production, reducing changeover time by 70%.
Protocol Integration: OPC UA Pub/Sub enables real-time communication between MES and equipment layers.
Lower Operational Costs: ARM reduces energy costs by 30%; remote diagnostics minimize on-site inspections.
Improved Productivity: Real-time anomaly response boosts overall equipment effectiveness (OEE) by 12%.
Scalability: Modular design supports future integration with 5G private networks or digital twin platforms.
This hardware-software integration is particularly suited for industries requiring high real-time performance and compact solutions, such as food packaging and semiconductor manufacturing, enabling low-TCO digital transformation of production lines.
