Getting vital equipment repaired quickly and accurately is an urgent priority, especially when those repairs are costly. Adaptive diagnostics can accelerate troubleshooting and boost first-time repair rates across very large populations of devices using interactive diagnostic procedures, resulting in greater operational efficiencies, improved uptime, lower costs, and faster warranty processing.
• Accelerates repair times and warranty processing with real-time detailed diagnostics, structured repair workflows, and accurate parts replacement for Improved operational efficiencies
• Improves repair quality, reduces repair return rates, and decreases human error
• Reduces Mean Time to Repair (MTTR) for improved uptime
• Lowers operational expenses by reducing service costs, overhead on technician staffing and training, and inventory maintenance and stock
DataV Repair uses holistic data analytics and machine learning to troubleshoot failures across millions of assets, dynamically prescribe diagnostic steps, and interactively guide technicians. It uses digital twins of assets to automatically process real-time and historical data to determine the probable root cause of an issue with high probability. It then evaluates fault codes, operating parameters, and current conditions to create an optimized repair plan that can be integrated into other enterprise applications such as service and maintenance systems. Armed with this detailed and accurate information, technicians can rapidly fix the problem right, the first time. Ongoing feedback loops of adaptive diagnostics and machine learning continually refine and improve repair processes and accuracy.