- 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
- 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
- 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
- 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
How to get started
We provide flexible engagement options to help you build predictive maintenance solutions faster. Contact us today to start with a workshop, discovery, or proof of concept (POC)
We offer free half-day workshops with our top experts in data science and predictive maintenance to discuss your processes, analytics tools and technologies, and opportunities for improvement.
If you have already identified a specific use case for anomaly detection, we can usually start with a 4‒8 week proof-of-concept project to deliver improvements and tangible results.
If you are in the requirements analysis and strategy development stage, we can start with a 2‒3 week discovery phase to identify the right use cases for predictive maintenance and anomaly detection, design your solution or product using industry best practices, and build a roadmap.