MEI productivity counting and line incident monitoring system is a set IoT Data Logger Developed on microcontroller platform STM32, specialized for collecting production data, monitoring operating status and analyzing the performance of automatic lines in the factory. Devices that support connection to Optical sensor, Encoder, limit switch, proximity sensor, Loadcell, signal Digital Input/Output and RS485 Modbus RTU, allowing integration with PLCs, inverters, HMIs and other industrial devices.
The STM32 controller performs high-speed signal collection, pulse product counting (Pulse Counter), anti-interference processing, anti-duplicate counting (Debounce), calculations of instantaneous output, output by shift, by day, machine running time (Run Time), machine downtime (Down Time), cycle time (Cycle Time), operating performance and indicators for evaluating line productivity.
Devices that support connection Ethernet (LAN), Wi-Fi or 4G LTE, transmit data to the platform MEI ECO through protocol MQTT, allowing real-time remote monitoring and control on Web/App. Users can configure production plans, target output, shift length, allowable downtime and alarm conditions appropriate to each line.
The system continuously monitors the machine's operating status and automatically detects problems such as: machine stoppage, loss of sensor signal, product jam, motor error, inverter error, failure to achieve output or exceeding cycle time. When an abnormality is detected, the device will record it Alarm Log, determine when the problem arose and send it Push Notification to the Web/App platform for operators to handle promptly.
To ensure data is not lost, the device integrates Offline Data Logging Using Flash/EEPROM, automatically stores all production data when network connection is lost and synchronizes to the server after the connection is restored. Platform MEI ECO Supports real-time Dashboard, productivity charts, shift statistics, incident history, user permissions and Export Excel report, meeting the requirements of digital transformation and production management in modern factories.