01-03-2013, 11:52 AM
MODELING AUTOMATED GUIDED VEHICLE SYSTEMS IN MATERIAL HANDLING
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ABSTRACT:
The study objectives are to 1) provide information regarding the use
and benefits of Automated Guided Vehicle (AGV) systems in manufacturing
environments, and 2) review the literature related to design, modeling and simulation
of AGV systems. We classify the tools utilized in design problems of AGV systems
as analytical and simulation-based tools. Then, give examples of both categories
from related literature.
Introduction
Material handling in manufacturing systems is becoming easier as the automated
machine technology is improved. Today’s rapid developments in technology
presents manufacturing firms a variety of alternatives for in-plant transportation. An
Automated Guided Vehicle (AGV) system is such an advanced material handling
system that involves a fleet of driverless vehicles (AGVs) which follow a guided
path and are controlled by a computer (Hammond, 1986). The aim of this study is to
1) provide information regarding the use of AGV systems in manufacturing
environments, and 2) review the literature related to design, modeling and simulation
of AGV systems.
Automated Guided Vehicle (AGV) Systems
A typical AGV consists of the frame, batteries, electrical system, drive unit, steering,
precision stop unit, on-board controller, communication unit, safety system, and
work platform. AGV systems are mainly used for distribution of materials in
warehouse environments, and movement of material to and from production areas
and storage areas in manufacturing facilities.
Basic Vehicle Types
Types of AGVs can be categorized as towing vehicles, pallet trucks, and unit-load
carriers. Towing vehicles pull a series of trailers that are attached to the vehicle.
The trailers are attached to and detached from the vehicle manually at the stations.
The vehicle does not have lifting capabilities nor a transfer mechanism. It can be
used for any type of load. Pallet trucks are used for palletized loads and can have
high lifting capabilities. They can pick up and deposit loads at the floor level. Unitload
carrier may carry single or multiple loads on their deck. Some are capable of
traveling sideways. The transfer mechanism of the carrier can be either an active or
passive conveyor, such as a roller, belt, or chain conveyor, or it may be a lift/lower
deck.
Benefits of an AGV System
According to case studies of AGV applications provided by the Material Handling
Institute (1993), benefits of building and using AGV systems include labor costs
saving, better schedule of WIP, flexible material handling, effective inventory control, greater quality assurance and safety, increased production, improved
utilization of space, and flexible routing.
AGV Systems Design Problem
Typical objectives in design of AGV systems include 1) evaluation of the feasibility
of an AGV system, 2) evaluation of the dispatching rules, 3) elimination of traffic
problems, 4) maximizing the throughput, 5) maximizing the vehicle utilization, 6)
minimizing the inventory level, 6) minimizing the transportation costs, and 7)
maximizing the space utilization. Tools used in AGV system design can be
classified in two main categories: analytical tools and simulation-based tools.
Analytical tools are mathematical techniques such as queuing theory, integer
programming, heuristic algorithm, and Markov Chains. A number of analytical
approaches to the design of AGV systems have been proposed in the literature.
Analytical tool
Tanchoco et al. (1987) compared the effectiveness of CAN-Q, an analytical model
based on queuing theory and used for analyzing work flows through a manufacturing
system, with a simulation-based model built in AGVSim (Egbelu and Tanchoco,
1982). CAN-Q underestimated the actual number of vehicles required. Their
analysis indicates that the results obtained through CAN-Q provide a good starting
point for the simulation study.
Bozer and Srinivasan (1991) introduced the concept of 'tandem configuration' to the
design of AGV systems. The tandem configuration is based on partitioning all of the
workcenters into non-overlapping, single vehicle closed loops. It offers less
complicated control systems, but has less tolerance for vehicle breakdowns and
requires additional floor space. The authors also developed an analytical model to
estimate the throughput capacity of a single vehicle in a closed loop. Mahadevan and
Narendran (1993) developed an analytical model for estimation of the number of
AGVs. They suggested to start with rough-cut analytical methods, followed by the
use of sophisticated mathematical models and then to apply simulation if the level of
complexity of the AGV system was high. As the number of parts in the system
increases, the problem becomes intractable and needs to be analyzed by simulation
method.
General-purpose Simulation Languages
Several AGV system simulation models have been developed using general-purpose
simulation languages such as SLAM II (Pritsker, 1995), SIMAN (Pegden et al.,
1990), and GPSS/H (Henriksen and Crane, 1989). Seifert et al. (1995) developed a
discrete-event simulation model written in SLAM II to analyze the operation of an
AGV system under a variety of vehicle routing strategies. Their model handled
multiple layouts and pedestrians in the system. It was a mixed-language model that
was written in SLAM II with event-processing functions written in the C
programming language. A specific performance measure was employed by their
simulation model. It was the difference between AGV's actual travel time and the
corresponding theoretical travel time of the AGV with respect to its speed and the
travel length.
Object-Oriented AGV Simulation Studies
In general, the above simulation programs specific for AGV systems are flexible and
reduce the complexity of the task of simulating AGV systems. However, they do not
offer flexibility, extensibility and reusability. King and Kim (1995) developed
AgvTalk, an object-oriented simulation tool for the design and analysis of AGV
system configuration and control. The model was composed of an AGV system, a
material handling system, production system, and an interface through which the
material handling system and the production system communicated with each other.
AgvTalk includes 25 object classes and more than 300 object methods in its library.
Smalltalk-80 has been used as the programming language. Window-based user
interface in AgvTalk is supported by MVC (Model-View-Controller) triad in
Smalltalk-80 (1990). Defining and changing the system requirements and
specifications is done by using Graphical User Interface in AgvTalk.
Conclusion
Automated guided vehicle systems are particularly useful in material handling in
manufacturing systems. Along with their increasing use, design problem of AGV
systems has been a major concern of study. Simulation is widely used to evaluate the
system performance for both real and proposed AGV systems. Many attempts have
been made for developing AGV simulators either for specific problems or as generic
--applicable to any AGV system--simulators. However, there is still a strong need
for a generic and extensible (by using object oriented programming approach) AGV
simulator with broad capabilities. Hence, future research efforts can be directed to
create such simulation systems.