Simulation of Autonomous Vehicle in Manufacturing

A Discrete Event Simulation (DES) approach was used to study and analyze the transition from a manual material handling system to an automated system of Autonomous Mobile Robots (AMRs) in a manufacturing plant. The plant currently relies on a manual system where a hand truck operator services multiple injection molding machines with varying cycle times, transporting parts bins to the warehouse. Transitioning to AMRs is expected to improve efficiency, reduce labor costs, and sustain high production rates. However, determining the optimal number of AMRs is critical to balancing operational efficiency with capital investment. Using the ARENA® simulation software, the project models the manufacturing floor to analyze machine cycle times, service requirements, and distances between tasks. The objective is to identify the minimum number of AMRs required to maintain seamless operations and high robot utilization while avoiding delays and overcapacity. The study ensures accurate and actionable insights by replicating real-world constraints and production metrics. The findings will provide a cost-effective, efficient solution for deploying AMRs, supporting the plant's transition to automated material handling. Keyword: Simulation modeling, Autonomous Mobile Vehicles, Material Handling in manufacturing

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Publication Details

Published
2025-06-17
DOI
https://doi.org/10.46254/na10.20250085
Primary Topic
Assembly Line Balancing Optimization
Type
article
Field-Weighted Citation Impact
0.00
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article

Simulation of Autonomous Vehicle in Manufacturing

M. Ali Montazer, Kasra Fatemi
Assembly Line Balancing Optimization
article

Simulation of Autonomous Vehicle in Manufacturing

M. Ali Montazer, Kasra Fatemi
article en

Abstract

A Discrete Event Simulation (DES) approach was used to study and analyze the transition from a manual material handling system to an automated system of Autonomous Mobile Robots (AMRs) in a manufacturing plant. The plant currently relies on a manual system where a hand truck operator services multiple injection molding machines with varying cycle times, transporting parts bins to the warehouse. Transitioning to AMRs is expected to improve efficiency, reduce labor costs, and sustain high production rates. However, determining the optimal number of AMRs is critical to balancing operational efficiency with capital investment. Using the ARENA® simulation software, the project models the manufacturing floor to analyze machine cycle times, service requirements, and distances between tasks. The objective is to identify the minimum number of AMRs required to maintain seamless operations and high robot utilization while avoiding delays and overcapacity. The study ensures accurate and actionable insights by replicating real-world constraints and production metrics. The findings will provide a cost-effective, efficient solution for deploying AMRs, supporting the plant's transition to automated material handling. Keyword: Simulation modeling, Autonomous Mobile Vehicles, Material Handling in manufacturing

Openalex Percentile: Top 63%
Assembly Line Balancing Optimization
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Simulation of Autonomous Vehicle in Manufacturing — M. Ali Montazer, Kasra Fatemi · (2025) | TGRS Research Map | TGRS