Predictive maintenance

Collecting the right data and transforming it into actionable insights

Hindsight informs action

You can’t expect to meet SLAs and KPIs if you simply react to problems as they occur. You must predict the problems and take a proactive approach to ensure they never happen. This requires capturing data from your fleet of robots and sensors, enhancing it with human intelligence and machine learning, and then using those insights to identify predictive trends, behavioral anomalies, and process improvements. Analyzing the data collected and utilizing the insights to construct automated and proactive workflows will significantly improve your fleet’s performance.

Identify trends faster with data in context

Formant’s data-centric approach to robot operations is uniquely suited to support proactive responses and predictive maintenance of your fleet of robotic resources. Data is captured from the robots, sensors, and field resources and analyzed against key business and operational metrics to highlight anomalies and trends. These insights inform process improvements and proactive maintenance schedules that are turned into event-triggered workflows that automatically address impending issues before they occur.
Eliminate unplanned downtime and improve OEE with proactive service.
Alert teams when sensitive machine components hit critical conditions.
Understand mean time to failure and determine accurate service timelines.
Protect or outperform on performance-based contracts for mission-critical areas.
Understand the impact of service degradations on maintaining throughput.
Determine the right time to invest in hardware system upgrades.

Explore our robot data and ops platform

Superior observability, operations, and analytics of heterogeneous fleets, at scale
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Canvas and Formant Case Study Image
How a construction company, Canvas, combined machine and human insights to create better outcomes.