Skip to content



The customer’s need was to understand if some of their production machinery (aged between 10 and 15 years) were easily upgradable and it was possible, with some changes, to analyze some important information of the production cycle such as temperature, humidity, brightness, etc..

The customer did not want to change the machines of this particular line (for reasons of certification and design) but only wanted to update them.

We worked on this study recreating to scale some machines of the production process of the customer.

  • Increased performance efficiency
  • Reduction of Corrective and Predictive Maintenance costs
  • Early problem forecasting
  • Reduction of production costs
  • Energy and maintenance cost savings


Thanks to our designers, we first analysed our customer’s system and created a model of the main machines found in the company. We created a “Steam Machine” and inserted some sensors: humidity, temperature, pressure, brightness.
With Microsoft integrated systems, we created an IOT Hub to capture all the information coming from the machines. These data, after being analyzed, studied and learned by our AI, were displayed on a dashboard thanks to the Microsoft Dynamics CRM platform.The on-site operator can associate a job directly without having to contact the technician. Thanks to the app loaded on his vehicle or portable device, the technician is always aware of the latest tickets assigned and work orders.


  • Sensors produce data
  • Profibus sensor concentrator
  • Siemens SPS (PLC)
  • AZURE IoT Hub Connector
  • Configurable device and system connectivity
  • Concentrate & harmonize sensor data (OMPP)
  • Field Gateway
  • Microsoft AZURE Platform
  • IoT Hub / Stream Analytics / Machine Learning
  • Cloud Gateway
  • Collect data
  • Analyse & interpret data
  • Anomaly detection
  • Trigger follow-up process


  • Industrial Automation, Automation
  • Steelmaking
  • Metalworking

Related Case