Smart Factory

CHALLENGE

This 400,000 m² industrial plant needed to monitor temperature, humidity, and utility consumption (water, energy, and gas). Previously, six operators worked in three shifts, manually recording data 24/7. This approach presented multiple challenges:

  • Errors in data collection due to manual readings.
  • Mistakes in transcription and data entry.
  • Repetitive and demotivating tasks for employees.

To improve accuracy, reduce operational costs, and optimize workforce efficiency, automation was necessary.

SOLUTION

We analyzed the plant’s manual readings and proposed three custom IoT devices to cover over 150 measurement points, all connected through a single strategically placed LoRaWAN gateway. A fully interactive online dashboard was designed to display the entire industrial complex and real-time readings from our LoRaWAN devices.

We analyzed the plant’s manual readings and proposed three custom IoT devices to cover over 150 measurement points, all connected through a single strategically placed LoRaWAN gateway. A fully interactive online dashboard was designed to display the entire industrial complex and real-time readings from our LoRaWAN devices.

This solution allowed the client to experience the benefits of IoT technology, leading to the expansion of monitoring with additional sensors tracking new variables, such as motor vibration, machine performance, and fluid pressure in pipelines.

This solution allowed the client to experience the benefits of IoT technology, leading to the expansion of monitoring with additional sensors tracking new variables, such as motor vibration, machine performance, and fluid pressure in pipelines.

RESULTS

As expected, both data accuracy and frequency improved significantly, exceeding initial expectations. After just one month of analysis, the client identified energy, temperature, and pressure losses, which were later confirmed and resolved by the maintenance teams.

Key benefits of the solution:Key benefits of the solution:

  • Increased data collection frequency from once per day to once per hour.
  • Consumption profiles were created thanks to high-frequency data.
  • Eliminated human errors with fully automated readings.
  • Data analysis revealed leaks, irregularities, and anomalies for proactive decision-making.