Roboworx launched advanced artificial intelligence (AI)-powered predictive analytics capabilities for its Robot Service Manager (RSM) software. This new predictive analytics capability moves robot maintenance from a reactive "break-fix" model to a more proactive, data-driven approach, reducing downtime, extending the robot’s useful life, and accelerating promised return on investment (ROI).
"With predictive analytics, we can now flag specific components for replacement based on usage levels across different models,” says Jeff Pittelkow, managing director at Roboworx. "When a technician heads to a site, the system tells them exactly what is likely to fail next. This enables us to anticipate issues instead of just reacting to them, which in turn helps keep the robots working at peak efficiency no matter the task.”
Key takeaways:
· The new RSM AI uses machine learning to analyze historical service data and real-time telemetry, allowing Roboworx to anticipate mechanical failures before they occur and streamline communication between technicians and clients. By combining service history with odometry data such as cycles completed, miles traveled (for autonomous mobile robots or AMRs), or units produced, RSM AI identifies patterns in component wear or usage.
· Beyond predictive modeling, RSM AI also solves the “data fatigue” common in field service. The AI-powered system automatically converts technical forms and checklists into easy-to-read summaries similar to a doctor’s after-visit brief. For example, facility managers can view a concise, plain-language summation of their robot’s “health” via a client portal while robot technicians know the exact server history, including recurring issues specific to each robot model, long before they arrive on site.
· In addition to the new AI-powered predictive analytics, RSM includes a single, unified view of preventative maintenance, break/fix events, outages and service history at both the robot and site level, including before and after photos of work performed; a comprehensive scheduling system to ensure expert robot technicians are dispatched and managed effectively and efficiently for periodic preventative maintenance as well as on-call break/fix; and full client access to these records and data, enabling full management visibility into field service operations of their robots.
"As robotic technology grows more complex, RSM AI has already proven to be an invaluable tool to ensure our experts deliver the most effective care before clients even know they need it," says Chris McNelis, VP of operations at Roboworx. "Technicians don't have to change how they work because the AI handles the reporting, allowing them to focus on the hardware while keeping the client fully informed."
