AI Digital Twin for Industrial Plant
Industrial production plant in Piedmont - 250 employees, 3 continuous production lines
-78% (from 180 to 40 hours/year)
Unplanned downtime
+2,100,000 EUR/year
Avoided lost production
-60%
Unnecessary maintenance interventions
+12% (parameter optimization)
Energy efficiency
+15 points (from 68% to 83%)
OEE (Overall Equipment Effectiveness)
The problem to solve
Unplanned machine downtime cost an average of 15,000 EUR/hour in lost production. Maintenance was purely reactive or based on fixed schedules, with 40% of scheduled interventions proving unnecessary and 25% of failures occurring unexpectedly. Unplanned downtime totaled 180 hours/year.
What we implemented
AI digital twin of the plant integrating data from 200+ IoT sensors (vibrations, temperature, pressure, energy consumption). The model predicts failures 72 hours in advance, suggests the optimal maintenance window, and simulates what-if scenarios to optimize production parameters. Real-time dashboard for the plant manager.
Measured impact
Unplanned downtime
-78% (from 180 to 40 hours/year)
Avoided lost production
+2,100,000 EUR/year
Unnecessary maintenance interventions
-60%
Energy efficiency
+12% (parameter optimization)
OEE (Overall Equipment Effectiveness)
+15 points (from 68% to 83%)
Timeline
16 weeks (6 IoT infrastructure + 4 AI model + 4 integration + 2 tuning)
Investment
120,000 - 180,000 EUR (Transition 5.0 up to 45% + certified energy savings)
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