Manufacturing units often struggle with unplanned equipment downtime, which leads to productivity losses and increased maintenance costs. Monitoring critical parameters such as pressure, temperature, vibration, and air quality is crucial for maintaining operational efficiency. However, traditional monitoring systems lacked real-time responsiveness and predictive maintenance capabilities, leaving factories vulnerable to sudden failures.

Wheelson developed a state-of-the-art Condition Monitoring System using microcontroller units (MCUs) to collect real-time data from critical sensors on the factory floor. This solution offered continuous monitoring, edge computing for real-time decision-making, and cloud integration for remote analysis, all of which helped our client move towards predictive maintenance and proactive equipment management.

Sensor Integration and Data Collection

The system connected to a wide range of industrial sensors (pressure, temperature, current, voltage, gas, liquid flow, air quality, and vibration) using I2C, UART, SPI, and ADC communication protocols. This enabled the collection of accurate, real-time data from the factory environment, providing an up-to-date view of equipment health and performance.

Edge Computing for Real-Time Control

The MCU functioned as an edge computing device, processing sensor data locally and making immediate decisions based on preset logic. If abnormal conditions such as high temperature or excess vibration were detected, the system automatically triggered actuators or alarms to prevent damage and ensure safety.

Cloud Data Transmission

Data from the sensors was transmitted to a cloud platform using the MQTT protocol, where it could be analyzed for trends, historical patterns, and predictive maintenance. Factory managers were able to monitor equipment performance remotely, helping to identify potential issues before they resulted in equipment failure.

Actuator Control for Preventive Action

The system could automatically control actuators or notify maintenance teams when pre-defined thresholds were crossed, providing real-time alerts and the ability to intervene when necessary. This reduced the need for manual inspections and improved overall response times.