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Case StudyMarch 17, 2026 5 min read

One Robot Per Building: A 5-Machine University Campus Fleet That Pays Back in 18 Months

A composite case study: sizing a five-strong PUDU CC1 Pro scrubber fleet across a multi-building campus, absorbing the term-time traffic surge, with the real payback math from our Fleet & ROI engine.

By WhichBot Team

PUDU CC1 Pro autonomous scrubber-dryer

Illustrative scenario.This case study is a composite built from real industry benchmarks and our Fleet & ROI engine, not a specific named customer. Figures are representative, not a guarantee.

A metropolitan university asked us a question every facilities team is now asking: with cleaner turnover running near 28% a year and a night crew that is hard to keep staffed, can autonomous scrubbers hold the line on presentation across a whole campus — and pay for themselves? We ran their real floor plan through the Fleet & ROI Planner. The answer was a five-machine PUDU CC1 Pro fleet — one robot per building — with an 18-month payback.

18 mo
Payback period
5× PUDU CC1 Pro
10,000 m²
Hard floor washed / night
across 5 buildings
A$9,500
Net monthly labour saved
night crew trimmed
70 dB
Quiet enough for evenings
runs around people

The brief

The campus isn't one big floor — it's five separate buildings, each with its own ground-floor common areas: a library and learning hub, a science and labs block, the central lecture theatres, a student union with a food court, and a sports and recreation centre. Together that came to about 10,000 m² of cleanable hard floor that had to be washed six nights a week in term, before 8am lectures.

The constraints were ordinary and unforgiving:

  • A six-hour evening window (6pm–midnight) — after the last classes, before the building alarms armed.
  • Term-time surge. In peak weeks footfall doubles, food-court spills spike, and rain drags grit across every atrium. The floors that matter get dirtier, not just walked-on.
  • People still around. Early evening isn't an empty building — anything cleaning here has to be quiet and safe near students.
  • No appetite for a machine that needs an operator walking beside it all night.
Campus common areas — one CC1 Pro (and dock) per building
Library & Hub98% coveredScience & Labs97% coveredLecture Theatres99% coveredUnion & Food Court94% coveredSports & Rec96% coveredDock/bldg

Each building gets its own robot and charging dock — no lift integration needed, since every unit works a single ground-floor level. The food court runs a touch lower on audited coverage (stickier, busier), so it's the zone we watch.

The shortlist

The floors need washing, so this is scrubber territory — a wet 4-in-1, not a dry sweeper. We sized three genuine contenders against the same 10,000 m² and the same six-hour window, on each machine's real (not brochure) throughput.

PUDU CC1 Pro autonomous scrubber-dryer
The PUDU CC1 Pro — 4-in-1 scrubber-dryer with a fast spot-cleaning mode that gives it ~2.5× the real daily output of the standard CC1.
ModelTypeReal outputRuntimeIndicative priceUnits for this campus
PUDU CC1 ProWet 4-in-1 scrubber~2,040 m²/day~5 h~A$32,8005
PUDU CC1Wet 4-in-1 scrubber~771 m²/day~5 h~A$30,10013
Gausium Scrubber 50 ProWet scrubber~540 m²/h (spec-derated)~3 h~A$70,6006

The cheaper CC1 looks tempting per unit — but its fleet-measured daily output is only ~771 m², so to actually sustain 2,000 m² a building every night you'd need thirteen of them. The CC1 Pro's fast spot-cleaning mode lifts its real daily output to ~2,040 m², which is why five units clear the same campus. The premium Gausium is a capable machine, but its 3-hour runtime forces a mid-window recharge and its price is more than double — so its payback lands far out.

Estimated payback by fleet option (this campus)
5× PUDU CC1 Pro18 months13× PUDU CC142 months6× Gausium 50 Pro45 months

Payback = upfront ÷ monthly labour saved (constant across options — same floors, same crew displaced). PUDU sized on fleet-measured daily output; Gausium on its spec derated ~40%. ±1 unit either way doesn't change the ranking. Shorter is better.

The numbers that matter

The fleet math closes cleanly. Each CC1 Pro washes its building's ~2,000 m² in about 3 hours of cleaning at its real ~650 m²/h — comfortably inside the 5-hour battery and the 6-hour window, on a single charge, with headroom for the term-time surge. Five robots, five buildings, one dock each.

Five CC1 Pro units at an indicative ~A$32,800 each (ex-GST) plus multi-site mapping and commissioning came to about A$171,000 upfront. On the labour side, washing 10,000 m² by hand is roughly 25 crew-hours a night at 400 m²/h. The robots don't erase the whole shift — a supervisor stays for exceptions, restrooms, stairs and detailing — but they displace about 10.5 hours of nightly floor-mopping labour, or about A$365 a night at A$35/hour fully loaded. Across ~26 term-time nights (six a week) that's roughly A$9,500 a month.

Cumulative net savings vs. upfront cost
-$171k$0k$171kbreak-even0mo12mo24mo36mo

Break-even at ~18.0 months on a $171,000 upfront outlay saving $9,500/month.

That lands break-even at 18 months — and, as always, the estimate understates the value of consistency. A robot doesn't skip the back corridor at 2am during exam-week crunch, so audited coverage held up when the campus was busiest, which is exactly when manual coverage used to slip.

Three lessons from the rollout

  1. Map every building, then re-map. Five buildings meant five mapping days — and a re-map each time a food-court layout or exam-hall setup changed. Budget it as recurring, not one-off.
  2. Dock placement is per-building. Parked by the entrance of each atrium rather than a back store-room, the docks recovered roughly 10% of effective runtime in dead travel time.
  3. The night role changes, it doesn't vanish. The remaining staffer stopped pushing a mop and started supervising five robots and handling the spills and spaces they can't — a better job, and the reason the saving is ~A$9,500, not the full manual shift.

Would it work for your campus?

The honest answer is "it depends on your building count, your window, and your wage rates" — which is exactly what the planner is for.

Frequently asked questions

How many cleaning robots does a university campus need?
In this composite, five PUDU CC1 Pro scrubbers — one per building — washed about 10,000 m² of ground-floor common-area hard floor each night across five buildings, inside a six-hour evening window. That's roughly 2,000 m² per robot per night, which sits just inside the CC1 Pro's fleet-measured daily output of ~2,040 m².
Why use a scrubber and not a sweeper on a campus?
Campus atria, food courts, corridors and library floors need washing — spills, tracked-in grit and foot-traffic grime — not just dust pickup. That's a job for a wet 4-in-1 scrubber like the PUDU CC1 Pro (which sweeps, vacuums, mops and scrubs). A dry sweeper such as the PUDU MT1 has no water or recovery tank and only lifts dust and debris.
Are cleaning robots quiet enough to run around students?
The PUDU CC1 Pro operates at about 70 dB — around the level of normal conversation — so it can run in the early-evening window while some students are still in common areas, not only after lock-up.
What's the payback on a campus cleaning-robot fleet?
About 18 months here: roughly A$171,000 upfront for five PUDU CC1 Pro units (indicative ~A$32,800 each, ex-GST) plus multi-site mapping, against about A$9,500 a month in displaced night-crew floor-washing labour.
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