The simulation design and analysis of a Flexible Manufacturing System with Automated Guided Vehicle System

This paper presents the simulation design and analysis of a Flexible Manufacturing System (FMS) with an Automated Guided Vehicle system (AGVs). To maximize the operating performance of FMS with AGVs, many parameters must be considered, including the number, velocity, and dispatching rule of AGV, par...

Full description

Saved in:
Bibliographic Details
Published in:Journal of manufacturing systems 2009-12, Vol.28 (4), p.115-122
Main Authors: Um, Insup, Cheon, Hyeonjae, Lee, Hongchul
Format: Article
Language:English
Subjects:
Applied sciences
Automated Guided Vehicle System
Decision theory. Utility theory
Evolution Strategy
Exact sciences and technology
Flexible Manufacturing System
Multi Objective Nonlinear Programming
Operational research and scientific management
Operational research. Management science
Simulation
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:This paper presents the simulation design and analysis of a Flexible Manufacturing System (FMS) with an Automated Guided Vehicle system (AGVs). To maximize the operating performance of FMS with AGVs, many parameters must be considered, including the number, velocity, and dispatching rule of AGV, part-types, scheduling, and buffer sizes. Of the various critical factors, we consider the following three: (1) minimizing the congestion; (2) minimizing the vehicle utilization; and (3) maximizing the throughput. In this paper, we consider the systematic analysis methods that combine a simulation-based analytic and optimization technique that is Multi-Objective Non-Linear Programming (MONLP) and Evolution Strategy (ES). MONLP determines the design parameters of the system through multi-factorial and regression analyses. ES is used to verify each parameter for simulation-based optimization. A validation test for the two methods is conducted. This method-based approach towards design yields the correct experimental results, ensures confidence in the specification of design parameters and supports a robust framework for analysis.
ISSN:0278-6125
1878-6642
DOI:10.1016/j.jmsy.2010.06.001