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Handling baggage systems availability improvement on airport

Aingura insights

Data Acquisition Data Acquisition
Preprocessing Preprocessing
Transformation Transformation

Sectors

Utilities Utilities

Applications

Maintenance Maintenance
Consumption Efficiency Consumption Efficiency

impact

  • Leveraging the existing control system.
  • Reduction of the number of sensors required to obtain the improvement.
  • Use of energy consumption to evaluate mechanical behavior

Developed AI Technologies

  • Online Machine Learning-based non-intrusive load monitoring.
  • Multi-consumer baseline generation

Challenges

  • Transformation of the current maintenance model based on catalog-based preventive (without considering actual use) and corrective maintenance (with the consequent system downtime, reduced availability and higher repair costs).
  • Use of a single measurement system to obtain data from a line (30 conveyors), applying Machine Learning algorithms for start-up differences identification and degradation tracking by high-speed  energy consumption measurement..

results

  • Reduction of unscheduled shutdowns (>80%).
  • Reduction of preventive maintenance cost (50%)
  • Reduction of corrective maintenance cost (20%).
  • Reduction of energy consumptions (5%).
  • PRI: 1,5 years
  • The system can also be used to improve other systems like elevators, automatic stairs, HVAC or pumps in the airport

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