Maximizing traffic flow of automated guided vehicles based on Jamology and applications

Kenji Kumagai,Seiichi Shin,Kenji Sawada

doi:10.1177/1687814018812299

Kenji Kumagai, Seiichi Shin + Show 1 more

Open Access

https://doi.org/10.1177/1687814018812299

Copy DOI

Abstract

This study aims to propose and investigate a theoretical maximum traffic flow method. Furthermore, we propose a merging timing control based on the results obtained from this method, which are verified using actual automated guided vehicles. The results (micro-level optimization) enable automated guided vehicles to achieve a fabrication level optimization (macro-level optimization). Engineers working in the field of automated guided vehicles have found that there is an optimal headway distance that achieves a maximum traffic throughput when automated guided vehicles operate with merging points. “Zipper merging” is known to be a suitable merging method resulting from “Jamology.” In this study, first, we will verify the results using the “Zipper merging” simulation model. Second, we develop a mathematical model and verify its simulations and experiments using actual automated guided vehicles. Finally, we develop a merging timing control to augment transfer flow and verify the effects using a small full fabrication simulation. We predict that this control will improve factory model throughput when used in practical applications.

Highlights

In semiconductor industries, wafers are processed using various pieces of equipment and transferred between equipment by automated guided vehicles (AGVs) in an automated material handling system (AMHS).[1]
This study considers that AGVs have a finite acceleration and deceleration and that AGVs’ positions are controlled by the AMHS controller
This study developed a mathematical model based on zipper merging for AGVs in an AMHS to achieve the optimal headway distance and maximum traffic flow

Summary

Introduction

Wafers are processed using various pieces of equipment and transferred between equipment by automated guided vehicles (AGVs) in an automated material handling system (AMHS).[1]. AGVs operate along rails in the AMHS (see Figure 1), which includes numerous intersections, such as merging and diverging points. Traffic jams occur at intersections where there is a gathering of AGVs, as shown in Several methods have been proposed to analyze and/or control the entire transportation system. These methods can be categorized into three approaches, which are simulation, statistical, and optimization based.

Objectives

Results

Conclusion