A 3PL fulfillment center running a 24-robot AMR fleet watched its uptime collapse from 97% to 81% in just four months — not because the robots broke down, but because nobody had built a maintenance program for them. Wheel tread went unmeasured. LiDAR lenses accumulated warehouse dust. Battery charge cycles went untracked. When Oxmaint's robotics and cobot maintenance tracking was deployed, every AMR became a managed asset with its own PM schedule, health score, and work order history. Twelve months later, fleet uptime stood at 99.6% — and has held there since. Book a demo to see how AMR fleet tracking works inside Oxmaint.
AMR Fleet Achieves 99.6% Uptime with Predictive Maintenance
24 autonomous mobile robots. A fulfillment center running three shifts. One structured maintenance system that turned a failing fleet into a benchmark operation.
The Operation Behind This Case Study
The facility is a 280,000 sq ft third-party logistics fulfillment center in the Southeast US, processing approximately 18,000 order lines per day across three shifts, 363 days per year. The AMR fleet — 24 units deployed for goods-to-person order picking — represented a $1.9M capital investment made 18 months before Oxmaint was deployed. The robots were managed through the OEM fleet management software for navigation and task dispatch. No CMMS tracked them as maintainable assets.
The maintenance team of 8 technicians managed all facility equipment — conveyor systems, dock doors, packaging lines, HVAC — but had no formal program for the AMR fleet. When a robot faulted, a technician responded. When it worked, it was assumed to be fine. That assumption was the source of every problem that followed. Sign up for Oxmaint to register your AMR fleet as managed assets today.
How a 97% Fleet Became an 81% Fleet in 16 Weeks
AMRs are designed for 50,000+ operating hours — but only with structured maintenance. Without it, the six critical component categories degrade simultaneously and silently until the cumulative impact becomes visible in uptime numbers that no longer support throughput targets.
Fleet uptime degraded 16 percentage points over 16 weeks with no structured maintenance program in place
No tread depth measurement schedule existed. Seven units had developed tread wear that caused odometry drift — the robot's self-reported position diverged from its actual position over long routes, accumulating positioning errors that caused pick station misses and emergency stops. Worn tyres were the single largest contributor to the 16-point uptime drop.
Warehouse particulate — cardboard dust, packing foam debris — had accumulated on 14 of 24 LiDAR sensor lenses. Contaminated lenses reduced detection range and accuracy, causing the robots to navigate more conservatively, slow down more frequently, and occasionally stop when detecting phantom obstacles. Cleaning took under 3 minutes per unit. No one had scheduled it.
Lithium-ion AMR batteries last 2,000–3,000 charge cycles when managed correctly. Deep discharge cycles below 15% state-of-charge accelerate cell degradation significantly. The fleet's charging protocol had never been configured for opportunity charging. Average fleet battery capacity had dropped to 76% of original — meaning each robot returned to charge more frequently, reducing effective fleet throughput by an estimated 11%.
When a robot faulted, the technician responding had no access to that unit's history — how many hours since its last wheel inspection, whether its battery had been flagged before, what sensors had been calibrated and when. Every fault was diagnosed from zero context. Mean time to resolve AMR faults averaged 47 minutes — not because the fixes were complex, but because the diagnostic process was always starting blind.
Three Capabilities That Rebuilt Fleet Uptime
Oxmaint's robotics maintenance tracking did not require replacing the OEM fleet management platform. It worked alongside it — adding the maintenance layer that the OEM software was never designed to provide.
All 24 AMR units were registered in Oxmaint as individual assets — each with its own serial number, battery ID, motor specs, wheel model, and sensor configuration. PM templates were built for all six critical component categories: drive wheels (monthly tread measurement), LiDAR sensors (bi-weekly lens cleaning and range verification), battery management (opportunity charge protocol configuration and quarterly capacity testing), bumper sensors (monthly response testing), navigation map (quarterly drift validation), and software (monthly update log). From day one, every AMR had a PM schedule as rigorous as any conveyor motor or dock leveler in the facility. Sign up for Oxmaint to register your AMR fleet as individual tracked assets.
Oxmaint introduced a per-unit fleet health score — a composite of battery capacity percentage, tread depth remaining, sensor calibration recency, and open work order count. Fleet managers could see at a glance which units were approaching a maintenance threshold before a fault event. When a fault did occur, Oxmaint's work order was automatically pre-populated with the faulting unit's full history — last PM dates, battery cycle count, prior fault log — giving the responding technician context in under 30 seconds instead of 47 minutes. Mean time to resolve dropped from 47 minutes to 11 minutes within six weeks of this capability going live. Book a demo to see the fleet health score dashboard.
With six months of structured maintenance data, Oxmaint's analytics surfaced fleet-level patterns invisible in the OEM platform. Three units consistently showed LiDAR contamination at twice the fleet average rate — all three were assigned to a picking zone with unusually high cardboard-cutting activity. Their cleaning interval was adjusted from bi-weekly to weekly. Battery capacity trending identified four units approaching the 70% capacity threshold — the replacement trigger point — four months in advance, allowing procurement to order replacement packs at standard pricing rather than expedited cost. Uptime reached 99.6% by Month 12 and the facility reported zero unplanned fleet-wide stoppages in Month 12's 363-day operational calendar.
12-Month Performance vs. Pre-Deployment Baseline
All metrics reflect the 12-month period after Oxmaint deployment, compared against the 12-month equivalent prior period at the same order volume.
| Performance Metric | Pre-Oxmaint | Post-Oxmaint | Change |
|---|---|---|---|
| Fleet uptime (24-unit average) | 81% | 99.6% | +18.6 pts |
| Mean time to resolve (MTTR) | 47 minutes | 11 minutes | 77% faster |
| Unplanned AMR stoppages | 312 events/yr | 14 events/yr | 96% reduction |
| PM completion rate (fleet-wide) | Not tracked | 94% | Programme created |
| Emergency parts spend | $84,000/yr | $19,000/yr | -77% |
| Battery capacity (fleet average) | 76% of original | 91% of original | +15 pts recovered |
| Order lines missed due to AMR downtime | ~4,200/yr | ~180/yr | 96% reduction |
| Throughput value recovered | Baseline | +$312,000/yr | Full fleet restored |
Swipe to view full table on mobile
"Before Oxmaint, our AMRs were black boxes. We knew when they were broken because throughput dropped. Now I can see the battery capacity trend for every unit, the next PM due date for every wheel set, and which zone is putting the most wear on sensors. That visibility is not just operational comfort — it's how we went from reactive firefighting to zero unplanned stoppages in Month 12."
— Director of Fulfillment Operations, 3PL Fulfillment Center, Southeast USAWhat a Complete AMR PM Programme Covers
These six component categories account for 95% of AMR downtime events across all fleet types. A structured PM programme covering all six in Oxmaint is what separates a 99%+ fleet from an 80% fleet within the same facility.
Monthly tread depth measurement at 4 points per wheel. Worn tread causes odometry drift — the most common cause of positioning errors and pick-station misses. Replacement threshold: below 3mm remaining tread.
Monthly inspectionBi-weekly lens cleaning with lint-free cloth and detection range verification against a fixed reference point. Contaminated lenses cause phantom stops and conservative navigation that reduces effective throughput by 8–12% before any fault event occurs.
Bi-weekly cleaningQuarterly capacity testing with replacement triggered below 70% of original capacity. Opportunity charging protocol configured to keep cells above 20% state-of-charge. Contact cleaning monthly. Deep discharge below 15% accelerates cell aging significantly.
Quarterly capacity testMonthly response testing against a fixed object at defined speeds. Degraded bumper sensitivity creates a safety exposure in human-robot shared environments and triggers more conservative fleet-wide speed limits from the fleet management system.
Monthly response testQuarterly map drift validation — comparing the robot's stored facility map against current physical layout. Rack moves, new barriers, and floor tape changes all create map drift that degrades route efficiency and increases emergency stop frequency.
Quarterly validationMonthly firmware and navigation software update logging per unit. Version mismatches between units in a fleet cause subtle coordination errors. Oxmaint tracks each unit's software version and flags units running behind the fleet baseline.
Monthly logReady to build this programme for your AMR fleet?
Oxmaint gives you pre-built PM templates for all six AMR component categories. Register your first unit in minutes.
AMR Fleet Maintenance Questions
Oxmaint works alongside your OEM fleet management platform — it does not replace it. Your fleet software handles navigation, task dispatch, and traffic management. Oxmaint adds the maintenance layer: PM schedules, work order history, fault context, and health scoring per unit. The two systems serve different functions, and most facilities connect them via API so fault events in the fleet platform automatically generate work orders in Oxmaint. Book a demo to see the integration setup for your specific fleet platform.
Each AMR unit is registered in Oxmaint with its own battery asset record — capturing battery model, installation date, and cycle count at initialization. Quarterly capacity test results are logged as work order completions, building a capacity trend line per unit over time. Oxmaint flags units approaching the 70% capacity replacement threshold automatically, giving procurement four to six weeks of lead time to order replacements at standard pricing. Sign up for Oxmaint to configure battery health tracking for your fleet from day one.
Oxmaint supports integration with major AMR fleet platforms including MiR Fleet, Fetch Robotics (Zebra), and Geek+ Fleet Management via API connectors, as well as WMS-level integrations for facilities where AMR operational data is aggregated through a warehouse execution system. Custom API connectors are available for proprietary fleet platforms. The integration allows fault events from the fleet platform to automatically create structured work orders in Oxmaint. Book a demo to discuss your specific AMR platform and integration pathway.
Yes — and this is one of the primary advantages. Oxmaint manages every asset class in a fulfillment or warehouse facility in a single system: AMRs, conveyors, packaging lines, dock levelers, HVAC, and facility infrastructure. Maintenance managers have one dashboard for all assets rather than switching between the fleet platform for robots and a separate system for everything else. AMR PM schedules, work orders, and health scores appear in the same view as the rest of the facility's maintenance programme. Sign up for Oxmaint to manage your full facility asset register in one place.
Your AMR Fleet Is a Capital Asset. Maintain It Like One.
A $1.9M fleet running at 81% uptime is not delivering $1.9M of value. It is delivering 81 cents of every dollar you invested. The gap between 81% and 99.6% is not hardware — it is a maintenance programme. Oxmaint gives you the PM templates, health scoring, fault-to-work-order automation, and fleet analytics to build that programme in days, not months. The 18.6 percentage points this facility recovered translated to $312,000 in annual throughput value. Your fleet has the same recovery waiting.
