The bearings behind data centre uptime

THE GROWING reliance on automation is adding a new layer of moving parts to data centres, which already depend on continuous mechanical motion in cooling and air-handling systems. From cooling and air-handling systems to inspection robots and automated monitoring equipment, these systems rely on bearings, joints and drive components that must operate reliably over long periods. As automation becomes more widespread, the reliability of these individual components becomes an increasingly important consideration.

Why more robotics means more moving parts

Traditional data centre infrastructure already depends on multiple rotating and moving components. Cooling fans operate continuously and pumps circulate coolant, while air-handling equipment relies on precise mechanical motion. Robotics adds a further layer of physical movement, often involving compact motors, articulated joints, drive wheels and positioning systems.

These robotics applications frequently require miniature, thin-section or instrument bearings rather than standard industrial bearings. Although physically small, they can have a significant influence on the performance of the equipment they support.

Recent research into autonomous data centre inspection robots shows why this matters. A 2026 study published in the International Journal of Advanced Robotic Systems reported that an autonomous robot system deployed across multiple data centres improved inspection efficiency by more than 50 per cent, completed more than 10,000 km of autonomous patrols and identified more than 1,200 equipment anomalies.

A failed bearing in a robotic inspection unit might not bring down an entire facility, but it can remove a critical monitoring function, requiring unplanned maintenance and creating gaps in inspection coverage that operators seek to minimise in highly automated environments.

Where bearings come in

When installed in data centres, robots can support efficiency, productivity and monitoring capability. However, each one also introduces additional bearings and drive components that can become new sources of failure. This is where the reliability challenge becomes clear. The more automated a data centre becomes, the more these small components matter.

In robotic equipment, this challenge starts with the mechanisms that enable movement. Miniature ball bearingssupport servo motors and actuators, while thin-section bearings are used in rotary joints where space and weight are limited. If the specification is wrong, the consequences can be significant: a stalled joint or seized actuator could take the robot out of service entirely.

The same challenge extends to equipment that supports environmental control. Fans, pumps and air-handling systems all depend on bearings that may be required to perform over long service intervals, making bearing life an important consideration when specifying these systems.

As data centres adopt more automated monitoring and inspection systems, the challenge becomes one of scale rather than just individual failure. Precision bearings support pan-tilt-zoom cameras, automated inspection devices and LiDAR-based monitoring systems, with sealed and corrosion-resistant designs helping protect them from dust, humidity and other contaminants. As inspection robots, automated monitoring systems and mobile monitoring platforms reduce manual intervention, the number of precision bearings operating continuously across a data centre also increases, making component reliability a key consideration.

Getting the specification right

Specify the wrong bearing, and the effects can snowball quickly. Excess friction can lead to faster wear, overheating and eventual mechanical failure, while a failed bearing in equipment such as a cooling fan can create wider maintenance and uptime issues. For this reason, bearing specification is increasingly treated as part of reliability planning rather than a routine purchasing decision.

The commercial impact of downtime also reinforces the need for reliability planning. Uptime Intelligence’s 2026 Annual Outage Analysis found that 57 per cent of respondents to its 2025 annual survey said their most recent major outage cost more than $100,000, while one in five said their most recent impactful outage cost more than $1 million.

Selecting bearings according to factors such as speed, load, temperature, contamination risk, lubrication life and maintenance accessibility can help identify potential problems at the design stage. Reviewing these considerations alongside uptime targets and service intervals allows bearing selection to become part of a wider reliability strategy, rather than simply a procurement matter.

As data centres become more automated, reliability must be considered across every part of the equipment they depend on. Bearings may be small components, but selecting the right ones is crucial. Treating bearing specification as part of the wider reliability strategy can help data centre operators reduce avoidable maintenance and keep critical equipment running.

Chris Johnson is managing director at SMB Bearings

www.smbbearings.com