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Autonomous Mobile Robot Fleet Sizing Calculator

The Autonomous Mobile Robot Fleet Sizing Calculator estimates how many AMRs are needed to handle a defined daily transport or service workload. It converts daily move demand into required robot-hours, then compares that demand with the productive capacity of one robot after accounting for scheduled operating hours and expected utilization. A peak-demand factor can be added when the busiest planning period is heavier than an average day.

This calculator is useful for early warehouse, factory, hospital, or material-flow planning before detailed simulation data is available. The key is to define one “move” consistently—for example, one completed point-to-point delivery or one finished mission—and use a moves-per-hour rate measured on the same basis. The result is rounded up to a whole robot because partial vehicles cannot satisfy a fleet requirement. Real deployments may also need spare units for charging, maintenance, traffic congestion, queueing, or service-level targets, so final fleet design should incorporate those operating constraints.

AMR fleet inputs

moves/day
moves/hr
hr/day
%
×
Result
—
Estimated AMRs required
Effective capacity per AMR—
Peak-adjusted workload—
Estimated spare capacity—

1. Enter daily move demand
Use the number of completed AMR missions or moves the operation must handle in one day.

2. Set measured move rate
Enter the average completed moves one robot can achieve per productive hour under comparable conditions.

3. Define productive hours
Exclude periods when the robot is unavailable for the counted work, such as planned maintenance or charging that is not already reflected in the rate.

4. Apply expected utilization
Use a realistic percentage to account for idle time, dispatch gaps, traffic, and other losses.

5. Add a peak factor
Use 1.00 for average demand or a value above 1.00 when sizing for a heavier planning day.

6. Review the rounded fleet size
The result rounds up to the next whole AMR and shows the capacity margin created by that rounding.

AMRs required = ceil[(Daily moves × Peak factor) ÷ (Moves per robot per hour × Productive hours × Utilization)]

Utilization is converted from a percentage to a decimal. The ceil function rounds any fractional requirement up to the next whole robot.

The model uses average throughput and does not explicitly simulate travel-distance variation, charger queues, traffic interactions, downtime, or dispatch priorities.

What the result means

The main result is the minimum whole-number AMR count indicated by the entered average productivity and peak-load assumptions.

For high service-level requirements, consider additional reserve capacity for charging, maintenance, congestion, and demand variability.

Given

  • 1,500 moves per day
  • 11 moves per robot per hour
  • 15 productive hours per day
  • 78% utilization
  • 1.20 peak demand factor

Calculation
Peak workload = 1,500 × 1.20 = 1,800 moves. Capacity per AMR = 11 × 15 × 0.78 = 128.7 moves/day. Fleet = ceil(1,800 ÷ 128.7) = 14 AMRs.

Result
14 AMRs

Fourteen robots provide enough modeled capacity to cover the peak-adjusted workload, before any separate redundancy policy is added.

What is one move in this calculator?

Define a move as one complete unit of robot work that matches your throughput data, such as a completed delivery mission. Do not mix pickup counts, travel legs, and complete missions in the same calculation.

Should charging time reduce productive hours or utilization?

It can be represented in either place, but avoid counting the same loss twice. If your measured moves-per-hour rate already includes charging interruptions, additional adjustments may overstate the loss.

Why does the result round up?

Fleet size must be a whole number. Even a calculated requirement of 9.1 robots means ten robots are needed under the stated assumptions.

Does peak factor replace a detailed hourly demand profile?

No. It is a compact way to add demand margin when detailed time-of-day simulation is unavailable. Large peaks, queueing constraints, or strict response times are better studied with a more detailed model.

Should I add a spare robot beyond the result?

That depends on uptime targets, maintenance strategy, charger design, and the cost of missing demand. This calculator gives a workload-based minimum under the entered assumptions, not a mandatory redundancy policy.