Citation: Gregor, M.; Hodoˇn, R.;
Grznár, P.; Mozol, Š. Design of a
System for Verification of Automatic
Guided Vehicle Routes Using
Computer Emulation. Appl. Sci. 2022,
12, 3397. https://doi.org/10.3390/
app12073397
Academic Editor:
Alexandre Carvalho
Received: 3 March 2022
Accepted: 24 March 2022
Published: 27 March 2022
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Article
Design of a System for Verification of Automatic Guided
Vehicle Routes Using Computer Emulation
Milan Gregor
1
, Róbert Hodoˇn
2
, Patrik Grznár
1,
* and Štefan Mozol
1
1
Department of Industrial Engineering, Faculty of Mechanical Engineering, University of Žilina,
Univerzitná 8215/1, 010 26 Žilina, Slovakia; milan.gregor@fstroj.uniza.sk (M.G.);
stefan.mozol@fstroj.uniza.sk (Š.M.)
2
Asseco CEIT, a.s., Univerzitná 8661/6A, 010 08 Žilina, Slovakia; robert.hodon@asseco-ceit.com
* Correspondence: patrik.grznar@fstroj.uniza.sk; Tel.: +421-41-513-2733
Abstract:
A frequent change in the manufacturing program caused by a change in customer require-
ments requires a logistics system in the company that can respond flexibly to these changes. In order
for business logistics to respond flexibly and optimally to the tasks created, a tool is needed to verify
the functionality of the entire process. This article, at its core, deals with the use of emulation in a
mixed environment of the real and virtual worlds as a tool for optimising automatic guided vehicle
(AGV) routes. The main objective of the article is the design of a system that allows verification of
AGV routes using computer emulation. The solution was created and programmed in the Tecnomatix
Plant Simulation program, in cooperation with AGV logistics supply tractors, and tested on a logistic
test circuit. The results show that the main area of application of such a solution is mainly in the
area of the capacity utilisation of the AGVs that are used in internal logistics processes. This solution
helps to cut down on the time it takes to design and optimise logistics operations as well as on the
time it takes to test logistics systems at full capacity before commencing production.
Keywords: logistics; Industry 4.0; simulation; emulation
1. Introduction
Current trends in manufacturing logistics development show that, in terms of logistics
system productivity, the fastest, cheapest, and most efficient system wins. Manufacturing
logistics can be defined as a system for managing the in-house movement of materials
and goods, for managing the movement of materials and products from suppliers to
the plant and to individual workplaces, and for the movement of products and semi-
finished products from workplaces and plants to the customer [
1
]. When creating logistics
chains, i.e., coordinating, connecting, and optimising material flow from the place of
production to the place of consumption, a range of activities such as transport, packaging,
material handling, and storage should be ensured [
2
]. While logistics equipment is used
to provide this, among the most widespread is the automatic guided vehicle (AGV). An
AGV is a computer-controlled cargo carrier that moves without an operator—the driver.
Their movement is controlled by a combination of software and guidance systems that
are based on sensors [
3
,
4
]. When logistics system designers design such a system, they
aim to incorporate flexibility into their characteristics in the form of rapid adaptation to
changing market conditions. The AGV as a system is also suitable for flexibility because its
movement path can be changed within minutes depending on the changing priorities of the
manufacturing system. The involvement of flexible logistics allows holding inventory at an
optimal level in terms of minimum costs and increases possibilities during the scheduling
process when unexpected events occur [
5
,
6
]. In order to achieve a certain degree of flexibility
and the possibility of the reconfiguration of logistics processes, the incorporation of digital
technologies contained in the concept of Industry 4.0 is essential. With the advent of digital
technologies, there was a breakthrough in industry that has been called the digital factory.
Appl. Sci. 2022, 12, 3397. https://doi.org/10.3390/app12073397 https://www.mdpi.com/journal/applsci
