[Challenge #02] What is the appropriate number of AGVs?

🚚 [Challenge #02] What is the appropriate number of AGVs?

A simulation experiment to find the balance between productivity and efficiency

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📦 Scenario Overview

In this challenge, we build a transport simulation using AGVs (Automated Guided Vehicles)
to determine the optimal number of AGVs required to meet the target production volume.

AGVs are at the heart of smart logistics, and estimating their fleet size is directly tied to system investment and production efficiency in real-world applications.

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🏗️ Basic Process Layout

 

Start → B → A → End

• AGVs are used to transfer products between each stage.
• A Marker is placed in front of each station to indicate AGV pickup/drop-off points.
• The Source feeds MUs at regular intervals.
• Processing times:
  • Stations in Area B: 60 seconds
  • Stations in Area A: 60 seconds
• AGV (AMR) settings:
  • Turning radius: 0m (pivot turn)
  • Capacity: 1 unit
  • AGV receives one command only from the AGVPool
  • After task completion, AGV always returns to AGVPool
• Simulation time: 7 days
• Daily production target: 600 units per day

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🎯 Experiment Objectives

• Measure Throughput changes based on the number of AGVs
• Run simulations using 1 to 4 AGVs
• Compare:
  • Idle Time
  • Waiting Time
  • Utilization
• Determine the minimum number of AGVs required to meet the target

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🧪 Experiment Template (Example)

AGV CountUnits per Day (UPD)Idle TimeWaiting TimeNotes

	UPD (Unit Per Day)
1대
2대
3대
4대

 

Please fill in the actual data after simulation.

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📊 Key Analysis Points

• Increasing the number of AGVs improves throughput up to a point
• Beyond a certain number, Idle Time increases disproportionately while efficiency drops
• The moment Waiting Time significantly decreases marks the ideal fleet size

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💬 Closing Thoughts

This exercise isn’t just about “how many AGVs to use” —
it's about comparing investment efficiency versus productivity through simulation.

This challenge reflects one of the most common real-world questions in smart logistics,
and future challenges will expand into topics like AGV scheduling, priority rules, and collision avoidance.