Predictive maintenance

Prevent failures and reduce operational and maintenance costs using data science and machine learning.

Our clients

Manufacturing
Finance
Hi-tech
Retail
Healthcare

Scenarios

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Vehicles
  • Collect near real-time telematic data from mining trucks and machinery, warehouse forklifts, and on-road vehicles
  • Optimize maintenance schedules and maintenance packages offered to vehicle owners
  • Accelerate responses to requests for roadside assistance with diagnostic and location data from connected vehicles
  • Optimize usage and charging patterns for EV vehicles

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Industrial robotics
  • Collect sensor data from assembly lines, heavy machinery, and robots
  • Receive health reports that measure servo stress over time
  • Identify early signs of mechanical failure and avoid major breakdowns 
  • Detect issues in early stages and prevent failure propagation
  • Estimate robot service life and optimize maintenance schedules and costs 
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Telecommunication networks
  • Collect bitrate data and that from temperature sensors, radio network controllers (RNCs), and other sources
  • Reduce unplanned emergency work and perform maintenance only when necessary
  • Increase network utilization and availability
  • Reduce operational expenses by increasing the operations team’s productivity
  • Reduce customer churn by improving the customer experience
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Smart buildings
  • Collect signals from gas, CO2, air pressure, noise, and vibration sensors  
  • Optimize regular inspections of equipment
  • Identify, repair, and replace any defective equipment parts before a major breakdown
  • Adjust controls for optimal performance and energy efficiency
  • Identify moving parts that need to be lubricated to reduce wear-and-tear

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