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ロボットか人か？

Commercial floor cleaning

Cleaner with a walk-behind autoscrubber vs Autonomous floor scrubber

Whirrworkによるモデル推計であり、事実ではありません。 方法論 · 予測の検証記録

人 · 年額$28,817Staff cleaner
ロボット · 年額$27,931Buy a robot scrubber
回収期間45 か月
逆転する年すでにBase-case year (earliest to latest across scenarios)

On these numbers it is close: decide on the things that are not cost. The robot would sit idle most of the time; it pays off at higher volume or longer hours. Payback is longer than three years, which is longer than many robot contracts and some robot companies.

アメリカ合衆国 · USD · BLS OEWS May 2025 national medians by SOC occupation

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作業量
仮定

Square feet scrubbed per day: a big-box store or small warehouse. Use yours.

仮定

Hours per day the floor is available for cleaning.

仮定

Cleaning days per month.

仮定

Active months per year.

人員
U.S. Bureau of Labor Statistics

BLS OEWS May 2025 national median hourly wage, SOC 37-2011.

U.S. Bureau of Labor Statistics

Wages and salaries were 70.0% of total employer compensation cost for private industry workers in June 2026 (ECEC), so total cost = wage / 0.70.

ilostat.ilo.org

Nominal 4.4% a year, 2015-2025 (ILOSTAT hourly earnings).

ISSA, as reproduced by Parish Supply

ISSA practical rate for a 20-inch walk-behind autoscrubber, sq ft per hour.

ロボット
仮定 Avidbots

Robot sq ft per hour relative to a person with a walk-behind scrubber. Vendor theoretical maxima are about 3.6x (Avidbots Neo 2: 33,583 ft²/h); real floors with turns, obstacles and tank changes run far below that.

算出値 RobotLAB (reseller)

Midpoint of RobotLAB's Gausium purchase range ($29,600-$95,880). Small units sit at the bottom, ride-on-class at the top.

MLive

Midpoint of the quoted $2,250-$2,900/month Avidbots Neo lease (January 2024).

算出値 RobotLAB (reseller)

Midpoint of Gausium RaaS $829-$2,669/month (36-month term).

仮定

Site mapping, training and docking setup per site.

仮定

Yearly maintenance and consumables (pads, squeegees, batteries) as a share of purchase price.

仮定

Useful life in years.

仮定

Share of the cleaning window the robot is actually cleaning (charging, tank changes).

仮定

Share of robot work lost to faults that a person has to cover.

仮定

Share of the area robots skip (corners, under racking, spills, stairs) that a person still cleans.

仮定

Minutes of staff time per robot-hour (start, empty, refill, rescue).

仮定

kWh per robot operating hour.

仮定

Electricity price per kWh (USD). Check your bill; energy is rarely a big line.

資金
仮定

Annual financing / discount rate. Nobody publishes yours; 8% is a round mid-2026 commercial borrowing guess.

仮定

Years in the NPV comparison.

仮定

Share of a human service price that is labour (rises with wages). Used to escalate and to adjust US service prices to other countries.

仮定

Share of a robot service price that is labour (pilot, technician). The rest is equipment, which learning curves make cheaper.

仮定

Share of a lease or RaaS fee that pays for hardware (learns down). The rest is service and support (moves with wages).

Download these results (CSV)

結果

選択肢月額年額Per unit (sq ft)初期費用回収期間Break-even utilisation5-year NPV vs baseline
人 Staff cleaner 比較の基準 $2,401$28,817$0.003— — — —
ロボット Buy a robot scrubber $2,328$27,931$0.003$64,740 45 か月 32%
Utilisation 34%
 $13,187
ロボット Lease a robot scrubber $3,175$38,098$0.004$2,000 なし 48%
Utilisation 34%
 -$30,439
ロボット Robot scrubber as a service $2,349$28,186$0.003$2,000 21 か月 33%
Utilisation 34%
 $10,298

What moves the answer most

Each bar shows the 5-year NPV of the best robot option when one input moves to the low or high end of its range, with the rest held at your values.

5-year NPV vs baseline: Buy a robot scrubber5-year NPV vs baseline: Buy a robot scrubberWorkloadlow value: 15000 → -$48,410high value: 100000 → $161,020Robot purchase pricelow value: 29600 → $57,223high value: 95880 → -$30,849Human output per hourlow value: 6500 → $55,248high value: 12000 → -$9,201Useful life or contractlow value: 3 → -$22,168high value: 7 → $25,219Hourly wagelow value: 14.168000000000001 → -$6,613high value: 21.252 → $32,988Work that stays humanlow value: 0.05 → $24,782high value: 0.3 → -$4,205Maintenance per yearlow value: 0.04 → $23,501high value: 0.15 → -$4,862Employer on-cost multiplierlow value: 1.2790000000000001 → $2,795high value: 1.579 → $23,579Supervisionlow value: 2 → $17,733high value: 15 → $2,960$13,187low valuehigh valueSource: Whirrwork Robot-or-Human model v1.0.0 (whirrwork.com/tools/robot-vs-human/commercial-floor-cleaning/). Modelled estimate, not a fact.

Cost per unit to 2035

Real terms (today's money). Robot hardware follows Wright's law; wages follow each country's history. Shaded band: robots-slow to robots-fast scenarios. Whirrworkによるモデル推計であり、事実ではありません。

Chart単位あたりの人件費 (基本), 単位あたりのロボット費用 (基本), 単位あたりのロボット費用 (ロボット：進歩が速い), 単位あたりのロボット費用 (ロボット：進歩が遅い). Source: Whirrwork Robot-or-Human model v1.0.0 (whirrwork.com/tools/robot-vs-human/commercial-floor-cleaning/). Modelled estimate, not a fact.$0.00$0.001$0.002$0.0032026202720282029203020312032203320342035USD / sq ftscenario range単位あたりの人件費 (基本)単位あたりのロボット費用 (基本)単位あたりのロボット費用 (ロボット：進歩が速い)単位あたりのロボット費用 (ロボット：進歩が遅い)Source: Whirrwork Robot-or-Human model v1.0.0 (whirrwork.com/tools/robot-vs-human/commercial-floor-cleaning/). Modelled…

逆転する年: すでに

What the spreadsheet misses

安全性
Fewer slips while floors are wet if the robot cleans after hours; a 300 kg machine near shoppers needs working sensors and sensible routes.
品質
Robots are consistent on open floor and log what they cleaned. They miss edges and spot spills unless someone follows up.
柔軟性
A cleaner handles bathrooms, bins and the unexpected; a scrubber scrubs.
Edge cases
Cluttered, changing layouts (pallets left in aisles) kill robot productivity fast.
Customer experience
Usually neutral to positive in stores; noise at night is a non-issue.
Jobs and redeployment
The common pattern is redeploying cleaners to detail work rather than cutting hours one-for-one; plan the redeployment before the robot arrives.
規制
No licence needed. Check lease terms for damage liability.

関連

このページの出典

注記と出典は英語です。英語版が正式な版です。

  1. ISSA 612 cleaning times: 20-inch walk-behind automatic scrubber about 9,274 sq ft per hour; wet mop about 1,333-1,429 ISSA, as reproduced by Parish Supply, 2026-10
  2. Neo 2 disc cleaning head technical specifications: maximum theoretical productivity 33,583 ft²/h (26-inch) Avidbots, 2026-10 · vendor
  3. Gausium autonomous scrubbers: purchase $29,600-$95,880; RaaS $829-$2,669/month on a 36-month term RobotLAB (reseller), 2026-10 · vendor
  4. Avidbots Neo lease $2,250-$2,900/month, as quoted by an Avidbots representative MLive, 2024-01
  5. Occupational Employment and Wage Statistics, May 2025 (median hourly wage by occupation) U.S. Bureau of Labor Statistics, 2025-05
  6. Employer Costs for Employee Compensation, June 2026: wages and salaries 70.0% of private-industry compensation (series CMU2020000000000P) U.S. Bureau of Labor Statistics, 2026-06
  7. Mean nominal hourly earnings of employees by sex and occupation (ISCO-08), DF_EAR_EHRA_SEX_OCU_CUR_NB ILOSTAT (International Labour Organization), from national labour force and earnings surveys, 2025
  8. Labour cost levels by NACE Rev. 2 activity (lc_lci_lev): Germany 2022-2025, total labour cost vs wages and salaries per hour Eurostat, 2025
  9. Rates and thresholds for employers 2025 to 2026 (employer Class 1 NIC 15% above £5,000) HM Revenue & Customs, 2025-04-06
  10. 令和6年賃金構造基本統計調査 (Basic Survey on Wage Structure 2024), table 1 by occupation Ministry of Health, Labour and Welfare, Japan (via e-Stat), 2024-06
  11. Average monthly earnings of employees by sex and economic activity, DF_EAR_EMTA_SEX_ECO_CUR_NB ILOSTAT (International Labour Organization), 2022
  12. Average annual wage of employed persons in urban units in 2024 (by position and by region) National Bureau of Statistics of China, 2025-05-20
  13. Euro foreign exchange reference rates (cross rates to USD), via Frankfurter European Central Bank, 2026-10-23
  14. Wright, T. P. (1936). Factors affecting the cost of airplanes. Journal of the Aeronautical Sciences, 3(4), 122-128 Journal of the Aeronautical Sciences, 1936
  15. Nagy, B., Farmer, J. D., Bui, Q. M., & Trancik, J. E. (2013). Statistical basis for predicting technological progress. PLoS ONE, 8(2), e52669 (62 technologies; Wright's law among the best hindcasters; errors grow with horizon) PLoS ONE, 2013