Roboworx, a leading robot field service organization, has introduced advanced AI-driven predictive analytics capabilities for its Robot Service Manager (RSM) software. With this major upgrade, the company is shifting robot maintenance away from the traditional reactive “break-fix” approach and toward a proactive, data-focused service model. As a result, businesses can significantly reduce robot downtime, extend equipment lifespan, and accelerate the return on investment (ROI) from automation deployments.
To support the growing complexity of robotic systems across industries, Roboworx is now leveraging machine learning to enhance how maintenance teams detect and prevent failures. Instead of waiting for mechanical issues to disrupt operations, the new RSM AI analyzes historical service records along with real-time telemetry data to anticipate problems before they occur.
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Moreover, the platform combines service history with odometry metrics such as cycles completed, miles traveled by autonomous mobile robots (AMRs), or total units produced. By identifying patterns in wear and component usage, RSM AI helps predict which parts may fail next and enables faster, more efficient repairs.
“With predictive analytics, we can now flag specific components for replacement based on usage levels across different models,” said 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.”
In addition to forecasting maintenance needs, RSM AI also tackles a major challenge in field service operations data fatigue. Often, technicians and clients are overwhelmed by complex technical reports and checklists. To simplify this, the AI system automatically converts service documentation into clear, easy-to-understand summaries, much like a doctor’s post-visit report.
For instance, facility managers can access plain-language updates about a robot’s health through a client portal, while technicians can review detailed service histories and recurring model-specific issues before arriving onsite. This improved communication helps both parties stay informed and aligned.
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Although RSM was publicly introduced in 2025, Roboworx has spent the past five years training and refining the software across multiple industries, including warehousing, cleaning, food service, and delivery robotics. Alongside predictive analytics, the platform also offers a unified view of preventive maintenance schedules, break/fix incidents, outages, and full service history complete with before-and-after work photos.
Companies using RSM have already reported up to a 93% reduction in break/fix calls and repair times shortened by as much as 50%, thanks to better technician preparation.
“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,” said 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.”
Notably, Roboworx is providing RSM at no additional cost to all partners, ensuring robot OEMs and end-users can maximize both the lifespan and ROI of their automation investments.
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