scholarly journals Simulation modelling of material handling using AGV

2021 ◽  
Vol 1199 (1) ◽  
pp. 012015
Author(s):  
M Dobrzanska ◽  
P Dobrzanski

Abstract Modern production systems are mainly characterized by, among others, the use of automated transport systems. One of the components of such transport systems are automated guided vehicles (AGV). These vehicles are primarily used in the material handling due to their greater efficiency, flexibility and lower operating costs. The main aim of the article is to present the possibility of using simulation modelling in the analysis of internal transport operations using automated guided vehicles.

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4919
Author(s):  
Monika Kosacka-Olejnik ◽  
Mariusz Kostrzewski ◽  
Magdalena Marczewska ◽  
Bogna Mrówczyńska ◽  
Paweł Pawlewski

In the Industry 4.0 era, the Digital Twin has become one of the most promising enabling technologies supporting material flow. Although the literature on the Digital Twin is becoming relatively well explored, including a certain number of review papers, the context of the Digital Twins application in internal transport systems has not been investigated so far. This paper thoroughly reviews the research on the Digital Twins applied in internal transport systems concerning major research trends within this research area and identification of future research directions. It provides clarification of various definitions related to the Digital Twin concept, including misconceptions such as a digital shadow, a digital model, and a digital mirror. Additionally, the relationships between terms such as material handling, material flow, and intralogistics in the context of internal transport systems coupled with the Digital Twin are explained. This paper’s contribution to the current state of the art of the Digital Twins is three-fold: (1) recognition of the most influential and high-impact journals, papers, and researchers; (2) identification of the major research trends related to the Digital Twins applications in internal transport systems, and (3) presentation of future research agendas in investigating Digital Twins applied for internal transport systems.


2019 ◽  
Vol 9 (1) ◽  
pp. 600-605 ◽  
Author(s):  
Gabriel Fedorko ◽  
Martin Vasil ◽  
Michaela Bartosova

AbstractIntra-plant transport systems within their operation directly impact on the performance of production systems. For their effective operation, it is, therefore, necessary to realize evaluation of operational performance and effectivity. For the realization of this type of evaluation, in addition to a wide range of sensors that can be difficult for installation and operation, we can also use indirect methods that are equally able to provide reliable operational characteristics. Indirect analytical methods are presented above all by the approach which is based on the use of simulation methods. The method of computer simulation provides a wide range of options for the evaluation of efficiency and performance. The paper describes the use of a simulation model created in the program Tecnomatix Plant Simulation for analyzing the supply of production workplaces within the MilkRun system.


2009 ◽  
Vol 410-411 ◽  
pp. 151-158 ◽  
Author(s):  
Dominik T. Matt

Build-to-order was once the only way in which products were made, but limited the market to only the rich buyers. Mass production contributed to a wider access to products, however with losses in individuality. Finally, mass customization aimed at holding out the promise of both, and “lean” concepts helped to (partly) make it a reality. However, the world has changed significantly since the first introduction of “lean” – especially in the most recent years. European companies are facing a growing international competition in volume markets due to the increasing economical and technical emancipation of low labour cost countries. While multinational enterprises are shifting their manufacturing activities to Far East to keep competitive in terms of costs, small and medium sized companies often have to leave their traditional market segments and retreat into niches. However, smaller production lot sizes and the increasing complexity of product programmes require innovative manufacturing strategies. According to several studies and empirical proves, less than 0,5% of a company’s production lead time is value adding, the bigger part of it is dedicated to waiting, handling and internal transport. This paper presents a new approach for the design of lean manufacturing support systems in make-to-order production systems that have to deal with a huge variety of product types and with high variations in demand. A special focus is given to the design of manual material handling and transport (MMHT) solutions. With the help of axiomatic design principles, a tree of design parameters is derived and translated into generally applicable design rules. With the help of a practical example from make-to-order industry, the validity of the methodology is illustrated.


Author(s):  
Carlos Llopis-Albert ◽  
Francisco Rubio ◽  
Francisco Valero

<p class="Textoindependiente21">The designing of an efficient warehouse management system is a key factor to improve productivity and reduce costs. The use of Automated Guided Vehicles (AVGs) in Material Handling Systems (MHS) and Flexible Manufacturing Systems (FMS) can help to that purpose. This paper is intended to provide insight regarding the technical and financial suitability of the implementation of a fleet of AGVs. This is carried out by means of a fuzzy set/qualitative comparative analysis (fsQCA) by measuring the level of satisfaction of managerial decision makers.</p>


Author(s):  
Taichi Chujo ◽  
Kosei Nishida ◽  
Tatsushi Nishi

Abstract In a modern large-scale fabrication, hundreds of vehicles are used for transportation. Since traffic conditions are changing rapidly, the routing of automated guided vehicles (AGV) needs to be changed according to the change in traffic conditions. We propose a conflict-free routing method for AGVs using reinforcement learning in dynamic transportation. An advantage of the proposed method is that a change in the state can be obtained as an evaluation function. Therefore, the action can be selected according to the states. A deadlock avoidance method in bidirectional transport systems is developed using reinforcement learning. The effectiveness of the proposed method is demonstrated by comparing the performance with the conventional Q learning algorithm from computational results.


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